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[GH-ISSUE #14423] [qwen3.5 local models] Error: 500 Internal Server Error on AMD Radeon AI Pro R9700 (ROCm error: invalid device function, SOLVE_TRI failed) #55876

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opened 2026-04-29 09:51:10 -05:00 by GiteaMirror · 30 comments
GiteaMirror commented 2026-04-29 09:51:10 -05:00
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Originally created by @e-strelock on GitHub (Feb 25, 2026).
Original GitHub issue: https://github.com/ollama/ollama/issues/14423

What is the issue?

The qwen3.5:35b model doesn't load due to the error

rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 (see log).

My other models (qwen3:8b/14b/30b/32b, glm-4.7-flash, etc.) load and work without problems.

However, the qwen3.5:35b model works on my hardware when using Vulkan.

I should also note that with the included libraries, the ROCm backend doesn't detect my graphics card at all (probably because I don't see the gfx12*.dat files in the included library). To run models through the ROCm backend, I installed the AMD HIP SDK and set the environment variable

ROCBLAS_TENSILE_LIBPATH=C:\Program Files\AMD\ROCm\7.1\bin\rocblas\library

to point to the rocblas libraries supplied with the HIP SDK, not the Ollama ones. With this setup, all models load and run, except qwen3.5:35b.

Ollama version 0.17.1-rc1.

Thank you.

Relevant log output

time=2026-02-25T21:09:34.059+03:00 level=INFO source=types.go:42 msg="inference compute" id=0 filter_id=1 library=ROCm compute=gfx1201 name=ROCm1 description="AMD Radeon AI PRO R9700" libdirs=ollama,rocm driver=60551.38 pci_id=0000:03:00.0 type=discrete total="31.9 GiB" available="31.9 GiB"
time=2026-02-25T21:09:34.059+03:00 level=INFO source=routes.go:1768 msg="vram-based default context" total_vram="31.9 GiB" default_num_ctx=32768

...

[GIN] 2026/02/25 - 21:11:00 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2026/02/25 - 21:11:01 | 200 |    1.1072729s |       127.0.0.1 | POST     "/api/show"
[GIN] 2026/02/25 - 21:11:01 | 200 |     93.6529ms |       127.0.0.1 | POST     "/api/show"
time=2026-02-25T21:11:02.043+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 55839"
time=2026-02-25T21:11:02.663+03:00 level=INFO source=cpu_windows.go:148 msg=packages count=1
time=2026-02-25T21:11:02.663+03:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=16 efficiency=0 threads=32
time=2026-02-25T21:11:02.705+03:00 level=WARN source=sched.go:452 msg="model architecture does not currently support parallel requests" architecture=qwen35moe
time=2026-02-25T21:11:02.728+03:00 level=INFO source=server.go:247 msg="enabling flash attention"
time=2026-02-25T21:11:02.729+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\Public\\AI\\ollama\\blobs\\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a --port 55844"
time=2026-02-25T21:11:02.732+03:00 level=INFO source=sched.go:491 msg="system memory" total="61.6 GiB" free="51.9 GiB" free_swap="58.4 GiB"
time=2026-02-25T21:11:02.732+03:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="31.4 GiB" free="31.9 GiB" minimum="457.0 MiB" overhead="0 B"
time=2026-02-25T21:11:02.732+03:00 level=INFO source=server.go:757 msg="loading model" "model layers"=41 requested=-1
time=2026-02-25T21:11:02.753+03:00 level=INFO source=runner.go:1411 msg="starting ollama engine"
time=2026-02-25T21:11:02.763+03:00 level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:55844"
time=2026-02-25T21:11:02.773+03:00 level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:16 GPULayers:41[ID:0 Layers:41(0..40)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-02-25T21:11:02.799+03:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35moe file_type=Q4_K_M name="" description="" num_tensors=1959 num_key_values=56
load_backend: loaded CPU backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon AI PRO R9700, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0
load_backend: loaded ROCm backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll
time=2026-02-25T21:11:02.833+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.AVX512=1 CPU.0.AVX512_VBMI=1 CPU.0.AVX512_VNNI=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98
ggml_cuda_compute_forward: SOLVE_TRI failed
ROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882
  err
C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error
time=2026-02-25T21:11:04.291+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:55844/load\": read tcp 127.0.0.1:55849->127.0.0.1:55844: wsarecv: An existing connection was forcibly closed by the remote host."
time=2026-02-25T21:11:04.291+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:55844/load\": dial tcp 127.0.0.1:55844: connectex: No connection could be made because the target machine actively refused it."
time=2026-02-25T21:11:04.292+03:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\Public\AI\ollama\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details"
[GIN] 2026/02/25 - 21:11:04 | 500 |    2.3547445s |       127.0.0.1 | POST     "/api/generate"
time=2026-02-25T21:11:04.305+03:00 level=ERROR source=server.go:304 msg="llama runner terminated" error="exit status 1"

OS

Windows 11 24H2

GPU

AMD Radeon AI Pro R9700 (gfx1201)

CPU

Ryzen 9 9950X

Ollama version

0.17.1-rc1, 0.17.1

HIP SDK

6.4.2, 7.1.1

Originally created by @e-strelock on GitHub (Feb 25, 2026). Original GitHub issue: https://github.com/ollama/ollama/issues/14423 ### What is the issue? The qwen3.5:35b model doesn't load due to the error rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 (see log). My other models (qwen3:8b/14b/30b/32b, glm-4.7-flash, etc.) load and work without problems. However, the qwen3.5:35b model works on my hardware when using Vulkan. I should also note that with the included libraries, the ROCm backend doesn't detect my graphics card at all (probably because I don't see the gfx12*.dat files in the included library). To run models through the ROCm backend, I installed the AMD HIP SDK and set the environment variable ROCBLAS_TENSILE_LIBPATH=C:\Program Files\AMD\ROCm\7.1\bin\rocblas\library to point to the rocblas libraries supplied with the HIP SDK, not the Ollama ones. With this setup, all models load and run, except qwen3.5:35b. Ollama version 0.17.1-rc1. Thank you. ### Relevant log output ```shell time=2026-02-25T21:09:34.059+03:00 level=INFO source=types.go:42 msg="inference compute" id=0 filter_id=1 library=ROCm compute=gfx1201 name=ROCm1 description="AMD Radeon AI PRO R9700" libdirs=ollama,rocm driver=60551.38 pci_id=0000:03:00.0 type=discrete total="31.9 GiB" available="31.9 GiB" time=2026-02-25T21:09:34.059+03:00 level=INFO source=routes.go:1768 msg="vram-based default context" total_vram="31.9 GiB" default_num_ctx=32768 ... [GIN] 2026/02/25 - 21:11:00 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2026/02/25 - 21:11:01 | 200 | 1.1072729s | 127.0.0.1 | POST "/api/show" [GIN] 2026/02/25 - 21:11:01 | 200 | 93.6529ms | 127.0.0.1 | POST "/api/show" time=2026-02-25T21:11:02.043+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 55839" time=2026-02-25T21:11:02.663+03:00 level=INFO source=cpu_windows.go:148 msg=packages count=1 time=2026-02-25T21:11:02.663+03:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=16 efficiency=0 threads=32 time=2026-02-25T21:11:02.705+03:00 level=WARN source=sched.go:452 msg="model architecture does not currently support parallel requests" architecture=qwen35moe time=2026-02-25T21:11:02.728+03:00 level=INFO source=server.go:247 msg="enabling flash attention" time=2026-02-25T21:11:02.729+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\Public\\AI\\ollama\\blobs\\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a --port 55844" time=2026-02-25T21:11:02.732+03:00 level=INFO source=sched.go:491 msg="system memory" total="61.6 GiB" free="51.9 GiB" free_swap="58.4 GiB" time=2026-02-25T21:11:02.732+03:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="31.4 GiB" free="31.9 GiB" minimum="457.0 MiB" overhead="0 B" time=2026-02-25T21:11:02.732+03:00 level=INFO source=server.go:757 msg="loading model" "model layers"=41 requested=-1 time=2026-02-25T21:11:02.753+03:00 level=INFO source=runner.go:1411 msg="starting ollama engine" time=2026-02-25T21:11:02.763+03:00 level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:55844" time=2026-02-25T21:11:02.773+03:00 level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:16 GPULayers:41[ID:0 Layers:41(0..40)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-02-25T21:11:02.799+03:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35moe file_type=Q4_K_M name="" description="" num_tensors=1959 num_key_values=56 load_backend: loaded CPU backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon AI PRO R9700, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0 load_backend: loaded ROCm backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll time=2026-02-25T21:11:02.833+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.AVX512=1 CPU.0.AVX512_VBMI=1 CPU.0.AVX512_VNNI=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang) rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed ROCm error: invalid device function current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882 err C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error time=2026-02-25T21:11:04.291+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:55844/load\": read tcp 127.0.0.1:55849->127.0.0.1:55844: wsarecv: An existing connection was forcibly closed by the remote host." time=2026-02-25T21:11:04.291+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:55844/load\": dial tcp 127.0.0.1:55844: connectex: No connection could be made because the target machine actively refused it." time=2026-02-25T21:11:04.292+03:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\Public\AI\ollama\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details" [GIN] 2026/02/25 - 21:11:04 | 500 | 2.3547445s | 127.0.0.1 | POST "/api/generate" time=2026-02-25T21:11:04.305+03:00 level=ERROR source=server.go:304 msg="llama runner terminated" error="exit status 1" ``` ### OS Windows 11 24H2 ### GPU AMD Radeon AI Pro R9700 (gfx1201) ### CPU Ryzen 9 9950X ### Ollama version 0.17.1-rc1, 0.17.1 ### HIP SDK 6.4.2, 7.1.1
GiteaMirror added the bug label 2026-04-29 09:51:10 -05:00
GiteaMirror commented 2026-04-29 09:51:12 -05:00
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@Avaruz commented on GitHub (Feb 25, 2026):

I have the same error:

llama_model_loader: loaded meta data with 56 key-value pairs and 1959 tensors from E:\Data\ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen35moe
llama_model_loader: - kv 1: general.file_type u32 = 15
llama_model_loader: - kv 2: general.parameter_count u64 = 35951822704
llama_model_loader: - kv 3: general.quantization_version u32 = 2
llama_model_loader: - kv 4: qwen35moe.attention.head_count u32 = 16
llama_model_loader: - kv 5: qwen35moe.attention.head_count_kv arr[u32,40] = [0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 2, ...
llama_model_loader: - kv 6: qwen35moe.attention.key_length u32 = 256
llama_model_loader: - kv 7: qwen35moe.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 8: qwen35moe.attention.value_length u32 = 256
llama_model_loader: - kv 9: qwen35moe.block_count u32 = 40
llama_model_loader: - kv 10: qwen35moe.context_length u32 = 262144
llama_model_loader: - kv 11: qwen35moe.embedding_length u32 = 2048
llama_model_loader: - kv 12: qwen35moe.expert_count u32 = 256
llama_model_loader: - kv 13: qwen35moe.expert_feed_forward_length u32 = 512
llama_model_loader: - kv 14: qwen35moe.expert_shared_feed_forward_length u32 = 512
llama_model_loader: - kv 15: qwen35moe.expert_used_count u32 = 8
llama_model_loader: - kv 16: qwen35moe.feed_forward_length u32 = 0
llama_model_loader: - kv 17: qwen35moe.full_attention_interval u32 = 4
llama_model_loader: - kv 18: qwen35moe.image_token_id u32 = 248056
llama_model_loader: - kv 19: qwen35moe.mrope_sections arr[i32,3] = [11, 11, 10]
llama_model_loader: - kv 20: qwen35moe.rope.dimension_count u32 = 64
llama_model_loader: - kv 21: qwen35moe.rope.freq_base f32 = 10000000.000000
llama_model_loader: - kv 22: qwen35moe.rope.mrope_interleaved bool = true
llama_model_loader: - kv 23: qwen35moe.rope.mrope_section arr[i32,3] = [11, 11, 10]
llama_model_loader: - kv 24: qwen35moe.ssm.conv_kernel u32 = 4
llama_model_loader: - kv 25: qwen35moe.ssm.group_count u32 = 16
llama_model_loader: - kv 26: qwen35moe.ssm.inner_size u32 = 4096
llama_model_loader: - kv 27: qwen35moe.ssm.state_size u32 = 128
llama_model_loader: - kv 28: qwen35moe.ssm.time_step_rank u32 = 32
llama_model_loader: - kv 29: qwen35moe.ssm.v_head_reordered bool = true
llama_model_loader: - kv 30: qwen35moe.vision.attention.head_count u32 = 16
llama_model_loader: - kv 31: qwen35moe.vision.block_count u32 = 27
llama_model_loader: - kv 32: qwen35moe.vision.deepstack_visual_indexes arr[i32,0] = []
llama_model_loader: - kv 33: qwen35moe.vision.embedding_length u32 = 1152
llama_model_loader: - kv 34: qwen35moe.vision.image_mean arr[f32,3] = [0.500000, 0.500000, 0.500000]
llama_model_loader: - kv 35: qwen35moe.vision.image_std arr[f32,3] = [0.500000, 0.500000, 0.500000]
llama_model_loader: - kv 36: qwen35moe.vision.longest_edge u32 = 16777216
llama_model_loader: - kv 37: qwen35moe.vision.num_channels u32 = 3
llama_model_loader: - kv 38: qwen35moe.vision.patch_size u32 = 16
llama_model_loader: - kv 39: qwen35moe.vision.shortest_edge u32 = 65536
llama_model_loader: - kv 40: qwen35moe.vision.spatial_merge_size u32 = 2
llama_model_loader: - kv 41: qwen35moe.vision.temporal_patch_size u32 = 2
llama_model_loader: - kv 42: qwen35moe.vision_end_token_id u32 = 248054
llama_model_loader: - kv 43: qwen35moe.vision_start_token_id u32 = 248053
llama_model_loader: - kv 44: tokenizer.chat_template str = {%- set image_count = namespace(value...
llama_model_loader: - kv 45: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 46: tokenizer.ggml.add_padding_token bool = false
llama_model_loader: - kv 47: tokenizer.ggml.eos_token_id u32 = 248046
llama_model_loader: - kv 48: tokenizer.ggml.eos_token_ids arr[i32,2] = [248046, 248044]
llama_model_loader: - kv 49: tokenizer.ggml.merges arr[str,247587] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 50: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 51: tokenizer.ggml.padding_token_id u32 = 248044
llama_model_loader: - kv 52: tokenizer.ggml.pre str = qwen35
llama_model_loader: - kv 53: tokenizer.ggml.scores arr[f32,248320] = [0.000000, 1.000000, 2.000000, 3.0000...
llama_model_loader: - kv 54: tokenizer.ggml.token_type arr[i32,248320] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 55: tokenizer.ggml.tokens arr[str,248320] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - type f32: 544 tensors
llama_model_loader: - type f16: 207 tensors
llama_model_loader: - type q4_K: 1115 tensors
llama_model_loader: - type q6_K: 93 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 22.22 GiB (5.31 BPW)
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe'
llama_model_load_from_file_impl: failed to load model
time=2026-02-25T16:14:52.476-04:00 level=INFO source=sched.go:473 msg="NewLlamaServer failed" model=E:\Data\ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="unable to load model: E:\Data\ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a"

<!-- gh-comment-id:3961788482 --> @Avaruz commented on GitHub (Feb 25, 2026): I have the same error: llama_model_loader: loaded meta data with 56 key-value pairs and 1959 tensors from E:\Data\ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = qwen35moe llama_model_loader: - kv 1: general.file_type u32 = 15 llama_model_loader: - kv 2: general.parameter_count u64 = 35951822704 llama_model_loader: - kv 3: general.quantization_version u32 = 2 llama_model_loader: - kv 4: qwen35moe.attention.head_count u32 = 16 llama_model_loader: - kv 5: qwen35moe.attention.head_count_kv arr[u32,40] = [0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 2, ... llama_model_loader: - kv 6: qwen35moe.attention.key_length u32 = 256 llama_model_loader: - kv 7: qwen35moe.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 8: qwen35moe.attention.value_length u32 = 256 llama_model_loader: - kv 9: qwen35moe.block_count u32 = 40 llama_model_loader: - kv 10: qwen35moe.context_length u32 = 262144 llama_model_loader: - kv 11: qwen35moe.embedding_length u32 = 2048 llama_model_loader: - kv 12: qwen35moe.expert_count u32 = 256 llama_model_loader: - kv 13: qwen35moe.expert_feed_forward_length u32 = 512 llama_model_loader: - kv 14: qwen35moe.expert_shared_feed_forward_length u32 = 512 llama_model_loader: - kv 15: qwen35moe.expert_used_count u32 = 8 llama_model_loader: - kv 16: qwen35moe.feed_forward_length u32 = 0 llama_model_loader: - kv 17: qwen35moe.full_attention_interval u32 = 4 llama_model_loader: - kv 18: qwen35moe.image_token_id u32 = 248056 llama_model_loader: - kv 19: qwen35moe.mrope_sections arr[i32,3] = [11, 11, 10] llama_model_loader: - kv 20: qwen35moe.rope.dimension_count u32 = 64 llama_model_loader: - kv 21: qwen35moe.rope.freq_base f32 = 10000000.000000 llama_model_loader: - kv 22: qwen35moe.rope.mrope_interleaved bool = true llama_model_loader: - kv 23: qwen35moe.rope.mrope_section arr[i32,3] = [11, 11, 10] llama_model_loader: - kv 24: qwen35moe.ssm.conv_kernel u32 = 4 llama_model_loader: - kv 25: qwen35moe.ssm.group_count u32 = 16 llama_model_loader: - kv 26: qwen35moe.ssm.inner_size u32 = 4096 llama_model_loader: - kv 27: qwen35moe.ssm.state_size u32 = 128 llama_model_loader: - kv 28: qwen35moe.ssm.time_step_rank u32 = 32 llama_model_loader: - kv 29: qwen35moe.ssm.v_head_reordered bool = true llama_model_loader: - kv 30: qwen35moe.vision.attention.head_count u32 = 16 llama_model_loader: - kv 31: qwen35moe.vision.block_count u32 = 27 llama_model_loader: - kv 32: qwen35moe.vision.deepstack_visual_indexes arr[i32,0] = [] llama_model_loader: - kv 33: qwen35moe.vision.embedding_length u32 = 1152 llama_model_loader: - kv 34: qwen35moe.vision.image_mean arr[f32,3] = [0.500000, 0.500000, 0.500000] llama_model_loader: - kv 35: qwen35moe.vision.image_std arr[f32,3] = [0.500000, 0.500000, 0.500000] llama_model_loader: - kv 36: qwen35moe.vision.longest_edge u32 = 16777216 llama_model_loader: - kv 37: qwen35moe.vision.num_channels u32 = 3 llama_model_loader: - kv 38: qwen35moe.vision.patch_size u32 = 16 llama_model_loader: - kv 39: qwen35moe.vision.shortest_edge u32 = 65536 llama_model_loader: - kv 40: qwen35moe.vision.spatial_merge_size u32 = 2 llama_model_loader: - kv 41: qwen35moe.vision.temporal_patch_size u32 = 2 llama_model_loader: - kv 42: qwen35moe.vision_end_token_id u32 = 248054 llama_model_loader: - kv 43: qwen35moe.vision_start_token_id u32 = 248053 llama_model_loader: - kv 44: tokenizer.chat_template str = {%- set image_count = namespace(value... llama_model_loader: - kv 45: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 46: tokenizer.ggml.add_padding_token bool = false llama_model_loader: - kv 47: tokenizer.ggml.eos_token_id u32 = 248046 llama_model_loader: - kv 48: tokenizer.ggml.eos_token_ids arr[i32,2] = [248046, 248044] llama_model_loader: - kv 49: tokenizer.ggml.merges arr[str,247587] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 50: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 51: tokenizer.ggml.padding_token_id u32 = 248044 llama_model_loader: - kv 52: tokenizer.ggml.pre str = qwen35 llama_model_loader: - kv 53: tokenizer.ggml.scores arr[f32,248320] = [0.000000, 1.000000, 2.000000, 3.0000... llama_model_loader: - kv 54: tokenizer.ggml.token_type arr[i32,248320] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 55: tokenizer.ggml.tokens arr[str,248320] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - type f32: 544 tensors llama_model_loader: - type f16: 207 tensors llama_model_loader: - type q4_K: 1115 tensors llama_model_loader: - type q6_K: 93 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 22.22 GiB (5.31 BPW) **llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe' llama_model_load_from_file_impl: failed to load model** time=2026-02-25T16:14:52.476-04:00 level=INFO source=sched.go:473 msg="NewLlamaServer failed" model=E:\Data\ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="unable to load model: E:\\Data\\ollama\\models\\blobs\\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a"
GiteaMirror commented 2026-04-29 09:51:12 -05:00
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@e-strelock commented on GitHub (Feb 25, 2026):

Just to clarify, I also had the "unknown model architecture: 'qwen35moe'" error with ollama version 0.17.0. After I installed 0.17.1-rc1, ollama recognizes the model architecture (and even runs it with the Vulkan backend), but it doesn't work with the ROCm backend. So I'm assuming these aren't the same error.

<!-- gh-comment-id:3961844374 --> @e-strelock commented on GitHub (Feb 25, 2026): Just to clarify, I also had the "unknown model architecture: 'qwen35moe'" error with ollama version 0.17.0. After I installed 0.17.1-rc1, ollama recognizes the model architecture (and even runs it with the Vulkan backend), but it doesn't work with the ROCm backend. So I'm assuming these aren't the same error.
GiteaMirror commented 2026-04-29 09:51:13 -05:00
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@e-strelock commented on GitHub (Feb 25, 2026):

I may have encountered the same error described here with qwen3-coder-next:

https://github.com/ggml-org/llama.cpp/issues/19442

Furthermore, this thread contains a link to a patch that fixes the issue in llama.cpp:

https://github.com/user-attachments/files/25215350/mi50_solve_tri_fix_main.patch

Maybe the developers could use it in ollama?

<!-- gh-comment-id:3961887476 --> @e-strelock commented on GitHub (Feb 25, 2026): I may have encountered the same error described here with qwen3-coder-next: https://github.com/ggml-org/llama.cpp/issues/19442 Furthermore, this thread contains a link to a patch that fixes the issue in llama.cpp: https://github.com/user-attachments/files/25215350/mi50_solve_tri_fix_main.patch Maybe the developers could use it in ollama?
GiteaMirror commented 2026-04-29 09:51:13 -05:00
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@DeverStyle commented on GitHub (Feb 25, 2026):

I have the same issue with qwen3.5:35b, qwen3:30b works fine.
RTX 6000 Pro, no idea how to get server logs. Using 0.17.0

llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe' llama_model_load_from_file_impl: failed to load model time=2026-02-25T20:43:51.949Z level=INFO source=sched.go:473 msg="NewLlamaServer failed" model=C:\Users\xxx\.ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="unable to load model: C:\\Users\\xxx\\.ollama\\models\\blobs\\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a"

<!-- gh-comment-id:3962017052 --> @DeverStyle commented on GitHub (Feb 25, 2026): I have the same issue with qwen3.5:35b, qwen3:30b works fine. RTX 6000 Pro, no idea how to get server logs. Using 0.17.0 `llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe' llama_model_load_from_file_impl: failed to load model time=2026-02-25T20:43:51.949Z level=INFO source=sched.go:473 msg="NewLlamaServer failed" model=C:\Users\xxx\.ollama\models\blobs\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a error="unable to load model: C:\\Users\\xxx\\.ollama\\models\\blobs\\sha256-d838916ba05b9d908e9c3fecf16273b942a99aae94d1725c3e9fdd772522cf1a"`
GiteaMirror commented 2026-04-29 09:51:14 -05:00
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@DeverStyle commented on GitHub (Feb 25, 2026):

0.17.1-rc2 works for me
https://github.com/ollama/ollama/releases/tag/v0.17.1-rc2

<!-- gh-comment-id:3962135147 --> @DeverStyle commented on GitHub (Feb 25, 2026): 0.17.1-rc2 works for me https://github.com/ollama/ollama/releases/tag/v0.17.1-rc2
GiteaMirror commented 2026-04-29 09:51:15 -05:00
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@dojoca commented on GitHub (Feb 25, 2026):

Similar issue for me - I have NVIDIA gpus though.

ollama | llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe'

<!-- gh-comment-id:3962973350 --> @dojoca commented on GitHub (Feb 25, 2026): Similar issue for me - I have NVIDIA gpus though. ollama | llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'qwen35moe'
GiteaMirror commented 2026-04-29 09:51:18 -05:00
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@LorenzGit commented on GitHub (Feb 26, 2026):

Same issue

<!-- gh-comment-id:3963060511 --> @LorenzGit commented on GitHub (Feb 26, 2026): Same issue
GiteaMirror commented 2026-04-29 09:51:19 -05:00
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@e-strelock commented on GitHub (Feb 26, 2026):

To test, I installed AMD HIP SDK 6.4.2. It appears to have the same issue with an invalid SOLVE_TRI function on the device.

<!-- gh-comment-id:3963111496 --> @e-strelock commented on GitHub (Feb 26, 2026): To test, I installed AMD HIP SDK 6.4.2. It appears to have the same issue with an invalid SOLVE_TRI function on the device.
GiteaMirror commented 2026-04-29 09:51:19 -05:00
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@e-strelock commented on GitHub (Feb 26, 2026):

The problem also persists with 0.17.1 release.

<!-- gh-comment-id:3968863455 --> @e-strelock commented on GitHub (Feb 26, 2026): The problem also persists with 0.17.1 release.
GiteaMirror commented 2026-04-29 09:51:20 -05:00
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@averkiev commented on GitHub (Feb 27, 2026):

The problem also persists with 0.17.1 release.

As well as in 0.17.4

<!-- gh-comment-id:3971130246 --> @averkiev commented on GitHub (Feb 27, 2026): > The problem also persists with 0.17.1 release. As well as in 0.17.4
GiteaMirror commented 2026-04-29 09:51:21 -05:00
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@yxj007 commented on GitHub (Feb 27, 2026):

Same problem in 0.17.4, unknown model architecture: 'qwen35moe'

<!-- gh-comment-id:3971362035 --> @yxj007 commented on GitHub (Feb 27, 2026): Same problem in 0.17.4, unknown model architecture: 'qwen35moe'
GiteaMirror commented 2026-04-29 09:51:21 -05:00
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@GlisseManTV commented on GitHub (Feb 27, 2026):

Same problem in 0.17.4, unknown model architecture: 'qwen35moe'

with ollama model or other one ?
I ran into this issue with unsloth model

<!-- gh-comment-id:3971712368 --> @GlisseManTV commented on GitHub (Feb 27, 2026): > Same problem in 0.17.4, unknown model architecture: 'qwen35moe' with ollama model or other one ? I ran into this issue with unsloth model
GiteaMirror commented 2026-04-29 09:51:22 -05:00
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@yxj007 commented on GitHub (Feb 27, 2026):

Same problem in 0.17.4, unknown model architecture: 'qwen35moe'

with ollama model or other one ? I ran into this issue with unsloth model

Yes, I encountered this problem with unsloth/Qwen3.5-122B-A10B-GGUF

<!-- gh-comment-id:3971910853 --> @yxj007 commented on GitHub (Feb 27, 2026): > > Same problem in 0.17.4, unknown model architecture: 'qwen35moe' > > with ollama model or other one ? I ran into this issue with unsloth model Yes, I encountered this problem with unsloth/Qwen3.5-122B-A10B-GGUF
GiteaMirror commented 2026-04-29 09:51:22 -05:00
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@e-strelock commented on GitHub (Feb 27, 2026):

Dear friends, I opened this bug because I encountered an issue in the ROCm backend (invalid function, error in SOLVE_TRI). It seems pretty obvious that the "unknown model architecture" issue that some of you are experiencing is a different problem. I kindly request that you create a separate issue about the "unknown model architecture". The fact that reports of a completely different bug are being posted in the same thread is certainly hindering the developers and reducing the likelihood that any of our issues will be resolved. Thanks.

<!-- gh-comment-id:3971990153 --> @e-strelock commented on GitHub (Feb 27, 2026): Dear friends, I opened this bug because I encountered an issue in the ROCm backend (**invalid function, error in SOLVE_TRI**). It seems pretty obvious that the "**unknown model architecture**" issue that some of you are experiencing is a different problem. I kindly request that you create a separate issue about the "unknown model architecture". The fact that reports of a **completely different bug** are being posted in the **same thread** is certainly hindering the developers and **reducing the likelihood that any of our issues will be resolved**. Thanks.
GiteaMirror commented 2026-04-29 09:51:23 -05:00
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@yxj007 commented on GitHub (Feb 27, 2026):

Dear friends, I opened this bug because I encountered an issue in the ROCm backend (invalid function, error in SOLVE_TRI). It seems pretty obvious that the "unknown model architecture" issue that some of you are experiencing is a different problem. I kindly request that you create a separate issue about the "unknown model architecture" issue. The fact that reports of a completely different bug are being posted in the same thread as mine is certainly hindering the developers and reducing the likelihood that any of our issues will be resolved. Thanks.

Sorry but I think I encountered same issue with you (my GPU is RX 7900 XTX, of course ROCm backend)

<!-- gh-comment-id:3972067970 --> @yxj007 commented on GitHub (Feb 27, 2026): > Dear friends, I opened this bug because I encountered an issue in the ROCm backend (**invalid function, error in SOLVE_TRI**). It seems pretty obvious that the "**unknown model architecture**" issue that some of you are experiencing is a different problem. I kindly request that you create a separate issue about the "unknown model architecture" issue. The fact that reports of a **completely different bug** are being posted in the **same thread** as mine is certainly hindering the developers and **reducing the likelihood that any of our issues will be resolved**. Thanks. Sorry but I think I encountered same issue with you (my GPU is RX 7900 XTX, of course ROCm backend)
GiteaMirror commented 2026-04-29 09:51:24 -05:00
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@e-strelock commented on GitHub (Feb 27, 2026):

The same problem remains with qwen3.5:27b.

Relevant log output

[GIN] 2026/02/27 - 17:41:14 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2026/02/27 - 17:41:14 | 200 |    146.4478ms |       127.0.0.1 | POST     "/api/show"
[GIN] 2026/02/27 - 17:41:14 | 200 |     95.2024ms |       127.0.0.1 | POST     "/api/show"
time=2026-02-27T17:41:14.812+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 62800"
time=2026-02-27T17:41:15.880+03:00 level=INFO source=cpu_windows.go:148 msg=packages count=1
time=2026-02-27T17:41:15.880+03:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=16 efficiency=0 threads=32
time=2026-02-27T17:41:15.921+03:00 level=WARN source=sched.go:452 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-02-27T17:41:15.945+03:00 level=INFO source=server.go:247 msg="enabling flash attention"
time=2026-02-27T17:41:15.946+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\Public\\AI\\ollama\\blobs\\sha256-7935de6e08f9444536d0edcacf19d2166b34bef8ddb4ac7ce9263ff5cad0693b --port 62804"
time=2026-02-27T17:41:15.948+03:00 level=INFO source=sched.go:491 msg="system memory" total="61.6 GiB" free="52.6 GiB" free_swap="59.5 GiB"
time=2026-02-27T17:41:15.948+03:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="31.4 GiB" free="31.9 GiB" minimum="457.0 MiB" overhead="0 B"
time=2026-02-27T17:41:15.948+03:00 level=INFO source=server.go:757 msg="loading model" "model layers"=65 requested=-1
time=2026-02-27T17:41:15.969+03:00 level=INFO source=runner.go:1411 msg="starting ollama engine"
time=2026-02-27T17:41:15.978+03:00 level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:62804"
time=2026-02-27T17:41:15.981+03:00 level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:16 GPULayers:65[ID:0 Layers:65(0..64)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-02-27T17:41:16.006+03:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35 file_type=Q4_K_M name="" description="" num_tensors=1307 num_key_values=53
load_backend: loaded CPU backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon AI PRO R9700, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0
load_backend: loaded ROCm backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll
time=2026-02-27T17:41:16.038+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.AVX512=1 CPU.0.AVX512_VBMI=1 CPU.0.AVX512_VNNI=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98
ggml_cuda_compute_forward: SOLVE_TRI failed
ROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882
  err
C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error
time=2026-02-27T17:41:17.497+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:62804/load\": read tcp 127.0.0.1:62808->127.0.0.1:62804: wsarecv: An existing connection was forcibly closed by the remote host."
time=2026-02-27T17:41:17.497+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:62804/load\": dial tcp 127.0.0.1:62804: connectex: No connection could be made because the target machine actively refused it."
time=2026-02-27T17:41:17.497+03:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\Public\AI\ollama\blobs\sha256-7935de6e08f9444536d0edcacf19d2166b34bef8ddb4ac7ce9263ff5cad0693b error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details"
[GIN] 2026/02/27 - 17:41:17 | 500 |    2.7949379s |       127.0.0.1 | POST     "/api/generate"
time=2026-02-27T17:41:17.510+03:00 level=ERROR source=server.go:304 msg="llama runner terminated" error="exit status 1"

OS

Windows 11 24H2 26100.7623

GPU

AMD Radeon AI Pro R9700 (gfx1201)

CPU

Ryzen 9 9950X

Ollama version

0.17.4

HIP SDK

7.1.1

<!-- gh-comment-id:3973333776 --> @e-strelock commented on GitHub (Feb 27, 2026): The same problem remains with qwen3.5:27b. ### Relevant log output ```shell [GIN] 2026/02/27 - 17:41:14 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2026/02/27 - 17:41:14 | 200 | 146.4478ms | 127.0.0.1 | POST "/api/show" [GIN] 2026/02/27 - 17:41:14 | 200 | 95.2024ms | 127.0.0.1 | POST "/api/show" time=2026-02-27T17:41:14.812+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 62800" time=2026-02-27T17:41:15.880+03:00 level=INFO source=cpu_windows.go:148 msg=packages count=1 time=2026-02-27T17:41:15.880+03:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=16 efficiency=0 threads=32 time=2026-02-27T17:41:15.921+03:00 level=WARN source=sched.go:452 msg="model architecture does not currently support parallel requests" architecture=qwen35 time=2026-02-27T17:41:15.945+03:00 level=INFO source=server.go:247 msg="enabling flash attention" time=2026-02-27T17:41:15.946+03:00 level=INFO source=server.go:431 msg="starting runner" cmd="C:\\Users\\Erast\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\Public\\AI\\ollama\\blobs\\sha256-7935de6e08f9444536d0edcacf19d2166b34bef8ddb4ac7ce9263ff5cad0693b --port 62804" time=2026-02-27T17:41:15.948+03:00 level=INFO source=sched.go:491 msg="system memory" total="61.6 GiB" free="52.6 GiB" free_swap="59.5 GiB" time=2026-02-27T17:41:15.948+03:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="31.4 GiB" free="31.9 GiB" minimum="457.0 MiB" overhead="0 B" time=2026-02-27T17:41:15.948+03:00 level=INFO source=server.go:757 msg="loading model" "model layers"=65 requested=-1 time=2026-02-27T17:41:15.969+03:00 level=INFO source=runner.go:1411 msg="starting ollama engine" time=2026-02-27T17:41:15.978+03:00 level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:62804" time=2026-02-27T17:41:15.981+03:00 level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:16 GPULayers:65[ID:0 Layers:65(0..64)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-02-27T17:41:16.006+03:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35 file_type=Q4_K_M name="" description="" num_tensors=1307 num_key_values=53 load_backend: loaded CPU backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon AI PRO R9700, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0 load_backend: loaded ROCm backend from C:\Users\Erast\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll time=2026-02-27T17:41:16.038+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.AVX512=1 CPU.0.AVX512_VBMI=1 CPU.0.AVX512_VNNI=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang) rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed ROCm error: invalid device function current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882 err C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error time=2026-02-27T17:41:17.497+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:62804/load\": read tcp 127.0.0.1:62808->127.0.0.1:62804: wsarecv: An existing connection was forcibly closed by the remote host." time=2026-02-27T17:41:17.497+03:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:62804/load\": dial tcp 127.0.0.1:62804: connectex: No connection could be made because the target machine actively refused it." time=2026-02-27T17:41:17.497+03:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\Public\AI\ollama\blobs\sha256-7935de6e08f9444536d0edcacf19d2166b34bef8ddb4ac7ce9263ff5cad0693b error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details" [GIN] 2026/02/27 - 17:41:17 | 500 | 2.7949379s | 127.0.0.1 | POST "/api/generate" time=2026-02-27T17:41:17.510+03:00 level=ERROR source=server.go:304 msg="llama runner terminated" error="exit status 1" ``` ### OS Windows 11 24H2 26100.7623 ### GPU AMD Radeon AI Pro R9700 (gfx1201) ### CPU Ryzen 9 9950X ### Ollama version 0.17.4 ### HIP SDK 7.1.1
GiteaMirror commented 2026-04-29 09:51:25 -05:00
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@fedamerd commented on GitHub (Mar 2, 2026):

Also getting the same issue with my RX 9070 and Qwen3.5:9b in Ollama 0.17.5 (NOT "unknown architecture", open a separate issue people). I'm on Windows 11 25H2 with AMD HIP SDK 7.1.1 (also pointing to this library using ROCBLAS_TENSILE_LIBPATH environment variable). Only experienced this with Qwen3.5 models.

server.log:

time=2026-03-02T18:57:49.787+01:00 level=INFO source=server.go:430 msg="starting runner" cmd="C:\\Users\\<username>\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 63371"
time=2026-03-02T18:57:50.671+01:00 level=INFO source=cpu_windows.go:148 msg=packages count=1
time=2026-03-02T18:57:50.671+01:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=8 efficiency=0 threads=16
time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:246 msg="enabling flash attention"
time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:430 msg="starting runner" cmd="C:\\Users\\<username>\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\<username>\\.ollama\\models\\blobs\\sha256-dec52a44569a2a25341c4e4d3fee25846eed4f6f0b936278e3a3c900bb99d37c --port 63378"
time=2026-03-02T18:57:50.784+01:00 level=INFO source=sched.go:491 msg="system memory" total="31.9 GiB" free="24.9 GiB" free_swap="25.1 GiB"
time=2026-03-02T18:57:50.784+01:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="14.3 GiB" free="14.7 GiB" minimum="457.0 MiB" overhead="0 B"
time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:757 msg="loading model" "model layers"=33 requested=-1
time=2026-03-02T18:57:50.813+01:00 level=INFO source=runner.go:1429 msg="starting ollama engine"
time=2026-03-02T18:57:50.834+01:00 level=INFO source=runner.go:1464 msg="Server listening on 127.0.0.1:63378"
time=2026-03-02T18:57:50.841+01:00 level=INFO source=runner.go:1302 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:4096 KvCacheType: NumThreads:8 GPULayers:33[ID:0 Layers:33(0..32)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-03-02T18:57:50.886+01:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35 file_type=Q4_K_M name="" description="" num_tensors=883 num_key_values=52
load_backend: loaded CPU backend from C:\Users\<username>\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon RX 9070, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0
load_backend: loaded ROCm backend from C:\Users\<username>\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll
time=2026-03-02T18:57:50.931+01:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98
ggml_cuda_compute_forward: SOLVE_TRI failed
ROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882
  err
C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error
time=2026-03-02T18:57:52.467+01:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:63378/load\": read tcp 127.0.0.1:63384->127.0.0.1:63378: wsarecv: En eksisterende tilkobling ble tvangslukket av den eksterne verten."
time=2026-03-02T18:57:52.467+01:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:63378/load\": dial tcp 127.0.0.1:63378: connectex: Kan ikke koble til fordi målmaskinen avslo tilkobling."
time=2026-03-02T18:57:52.467+01:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\<username>\.ollama\models\blobs\sha256-dec52a44569a2a25341c4e4d3fee25846eed4f6f0b936278e3a3c900bb99d37c error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details"
[GIN] 2026/03/02 - 18:57:52 | 500 |    3.0694766s |  192.168.50.214 | POST     "/api/chat"
time=2026-03-02T18:57:52.482+01:00 level=ERROR source=server.go:303 msg="llama runner terminated" error="exit status 1"
<!-- gh-comment-id:3986074787 --> @fedamerd commented on GitHub (Mar 2, 2026): Also getting the same issue with my RX 9070 and Qwen3.5:9b in Ollama 0.17.5 (NOT "unknown architecture", open a separate issue people). I'm on Windows 11 25H2 with AMD HIP SDK 7.1.1 (also pointing to this library using ROCBLAS_TENSILE_LIBPATH environment variable). Only experienced this with Qwen3.5 models. server.log: ```text time=2026-03-02T18:57:49.787+01:00 level=INFO source=server.go:430 msg="starting runner" cmd="C:\\Users\\<username>\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --port 63371" time=2026-03-02T18:57:50.671+01:00 level=INFO source=cpu_windows.go:148 msg=packages count=1 time=2026-03-02T18:57:50.671+01:00 level=INFO source=cpu_windows.go:195 msg="" package=0 cores=8 efficiency=0 threads=16 time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:246 msg="enabling flash attention" time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:430 msg="starting runner" cmd="C:\\Users\\<username>\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --ollama-engine --model C:\\Users\\<username>\\.ollama\\models\\blobs\\sha256-dec52a44569a2a25341c4e4d3fee25846eed4f6f0b936278e3a3c900bb99d37c --port 63378" time=2026-03-02T18:57:50.784+01:00 level=INFO source=sched.go:491 msg="system memory" total="31.9 GiB" free="24.9 GiB" free_swap="25.1 GiB" time=2026-03-02T18:57:50.784+01:00 level=INFO source=sched.go:498 msg="gpu memory" id=0 library=ROCm available="14.3 GiB" free="14.7 GiB" minimum="457.0 MiB" overhead="0 B" time=2026-03-02T18:57:50.784+01:00 level=INFO source=server.go:757 msg="loading model" "model layers"=33 requested=-1 time=2026-03-02T18:57:50.813+01:00 level=INFO source=runner.go:1429 msg="starting ollama engine" time=2026-03-02T18:57:50.834+01:00 level=INFO source=runner.go:1464 msg="Server listening on 127.0.0.1:63378" time=2026-03-02T18:57:50.841+01:00 level=INFO source=runner.go:1302 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:4096 KvCacheType: NumThreads:8 GPULayers:33[ID:0 Layers:33(0..32)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-03-02T18:57:50.886+01:00 level=INFO source=ggml.go:136 msg="" architecture=qwen35 file_type=Q4_K_M name="" description="" num_tensors=883 num_key_values=52 load_backend: loaded CPU backend from C:\Users\<username>\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon RX 9070, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: 0 load_backend: loaded ROCm backend from C:\Users\<username>\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll time=2026-03-02T18:57:50.931+01:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang) rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed ROCm error: invalid device function current device: 0, in function ggml_cuda_compute_forward at C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:2882 err C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:94: ROCm error time=2026-03-02T18:57:52.467+01:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:63378/load\": read tcp 127.0.0.1:63384->127.0.0.1:63378: wsarecv: En eksisterende tilkobling ble tvangslukket av den eksterne verten." time=2026-03-02T18:57:52.467+01:00 level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:63378/load\": dial tcp 127.0.0.1:63378: connectex: Kan ikke koble til fordi målmaskinen avslo tilkobling." time=2026-03-02T18:57:52.467+01:00 level=INFO source=sched.go:518 msg="Load failed" model=C:\Users\<username>\.ollama\models\blobs\sha256-dec52a44569a2a25341c4e4d3fee25846eed4f6f0b936278e3a3c900bb99d37c error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details" [GIN] 2026/03/02 - 18:57:52 | 500 | 3.0694766s | 192.168.50.214 | POST "/api/chat" time=2026-03-02T18:57:52.482+01:00 level=ERROR source=server.go:303 msg="llama runner terminated" error="exit status 1" ```
GiteaMirror commented 2026-04-29 09:51:25 -05:00
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@kz26 commented on GitHub (Mar 2, 2026):

Running into the same issues with latest ollama 0.17.5, Windows 11 x64 25H2, RX 9070 XT with latest AMD 26.2.2 drivers. Can confirm that other (older) models work including Qwen 3 VL and InternVL 3.5. I've tried both the ollama-hosted Qwen 3.5 releases at https://ollama.com/library/qwen3.5:9b as well as the latest unsloth quants that were released today, both result in 500 errors.

<!-- gh-comment-id:3986176490 --> @kz26 commented on GitHub (Mar 2, 2026): Running into the same issues with latest ollama 0.17.5, Windows 11 x64 25H2, RX 9070 XT with latest AMD 26.2.2 drivers. Can confirm that other (older) models work including Qwen 3 VL and InternVL 3.5. I've tried both the ollama-hosted Qwen 3.5 releases at https://ollama.com/library/qwen3.5:9b as well as the latest unsloth quants that were released today, both result in 500 errors.
GiteaMirror commented 2026-04-29 09:51:26 -05:00
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@mizaar666 commented on GitHub (Mar 2, 2026):

Windows 11, RX9070XT, 0.17.5
The same issue, Vulkan backend works fine. But the latest AMD HIP libraries and video drivers throws

rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98
ggml_cuda_compute_forward: SOLVE_TRI failed
<!-- gh-comment-id:3987695299 --> @mizaar666 commented on GitHub (Mar 2, 2026): Windows 11, RX9070XT, 0.17.5 The same issue, Vulkan backend works fine. But the latest AMD HIP libraries and video drivers throws ``` rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed ```
GiteaMirror commented 2026-04-29 09:51:27 -05:00
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@aibin8910 commented on GitHub (Mar 8, 2026):

Windows11，AMD Radeon AI Pro R9700 x2，0.17.7版本，加载qwen3.5:35b模型出错，在Vulkan上也是正常的，也出现了如下错误，AMD HIP SDK 7.1.1和6.4.2都尝试过,无法解决。

rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed

Error: 500 Internal Server Error: model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details

<!-- gh-comment-id:4018344118 --> @aibin8910 commented on GitHub (Mar 8, 2026): Windows11，AMD Radeon AI Pro R9700 x2，0.17.7版本，加载qwen3.5:35b模型出错，在Vulkan上也是正常的，也出现了如下错误，AMD HIP SDK 7.1.1和6.4.2都尝试过,无法解决。 `rocBLAS error from hip error code: 'hipErrorInvalidDeviceFunction':98 ggml_cuda_compute_forward: SOLVE_TRI failed` `Error: 500 Internal Server Error: model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details`
GiteaMirror commented 2026-04-29 09:51:28 -05:00
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@e-strelock commented on GitHub (Mar 8, 2026):

Yesterday I tried experimental Vulkan support one more time with Ollama 0.17.7 as a temporary workaround for my AMD Radeon AI Pro R9700 by setting HIP_VISIBLE_DEVICES=-1 and OLLAMA_VULKAN=1. It worked (qwen3, qwen3moe, qwen3.5, qwen3.5moe, glmmoe).

<!-- gh-comment-id:4018803699 --> @e-strelock commented on GitHub (Mar 8, 2026): Yesterday I tried experimental Vulkan support one more time with Ollama 0.17.7 as a temporary workaround for my AMD Radeon AI Pro R9700 by setting `HIP_VISIBLE_DEVICES=-1` and `OLLAMA_VULKAN=1`. It worked (qwen3, qwen3moe, qwen3.5, qwen3.5moe, glmmoe).
GiteaMirror commented 2026-04-29 09:51:28 -05:00
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@Jasdfgh commented on GitHub (Mar 15, 2026):

this looks like the SOLVE_TRI issue with DeltaNet models. Qwen3.5 35b hits a triangular solve in rocBLAS that gfx1201 maybe doesn't have proper kernels for yet. same pattern shows up in llama.cpp issues on other AMD GPUs too.

Vulkan makes sense as a workaround since it bypasses rocBLAS entirely. probably the safest path for now.

fyi this likely affects all DeltaNet-based models (Qwen3.5 MoE family), not just 35b.

<!-- gh-comment-id:4063525083 --> @Jasdfgh commented on GitHub (Mar 15, 2026): this looks like the SOLVE_TRI issue with DeltaNet models. Qwen3.5 35b hits a triangular solve in rocBLAS that gfx1201 maybe doesn't have proper kernels for yet. same pattern shows up in llama.cpp issues on other AMD GPUs too. Vulkan makes sense as a workaround since it bypasses rocBLAS entirely. probably the safest path for now. fyi this likely affects all DeltaNet-based models (Qwen3.5 MoE family), not just 35b.
GiteaMirror commented 2026-04-29 09:51:29 -05:00
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@e-strelock commented on GitHub (Mar 16, 2026):

I can confirm that the dense models of the Qwen 3.5 family (qwen3.5:9b, qwen3.5:27b) have the same issue with SOLVE_TRI.

If someone with a Windows environment set up for compiling Ollama could build an experimental version of ggml-hip.dll using the patch from the llama.cpp project:

https://github.com/user-attachments/files/25215350/mi50_solve_tri_fix_main.patch

I would be willing to test it.

<!-- gh-comment-id:4066430922 --> @e-strelock commented on GitHub (Mar 16, 2026): I can confirm that the dense models of the Qwen 3.5 family (qwen3.5:9b, qwen3.5:27b) have the same issue with SOLVE_TRI. If someone with a Windows environment set up for compiling Ollama could build an experimental version of `ggml-hip.dll` using the patch from the llama.cpp project: https://github.com/user-attachments/files/25215350/mi50_solve_tri_fix_main.patch I would be willing to test it.
GiteaMirror commented 2026-04-29 09:51:30 -05:00
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@Jasdfgh commented on GitHub (Mar 18, 2026):

interesting that 9b and 27b also hit SOLVE_TRI. previous reports were all on 35b-a3b (MoE/DeltaNet), if the dense models trigger it too then the SOLVE_TRI kernel on gfx1201 is probably just broken in the bundled rocBLAS, not specific to DeltaNet.

I don't have a Windows build environment to compile that patch unfortunately. Vulkan is probably still the safest workaround until ollama ships with newer ROCm libs.

<!-- gh-comment-id:4079907675 --> @Jasdfgh commented on GitHub (Mar 18, 2026): interesting that 9b and 27b also hit SOLVE_TRI. previous reports were all on 35b-a3b (MoE/DeltaNet), if the dense models trigger it too then the SOLVE_TRI kernel on gfx1201 is probably just broken in the bundled rocBLAS, not specific to DeltaNet. I don't have a Windows build environment to compile that patch unfortunately. Vulkan is probably still the safest workaround until ollama ships with newer ROCm libs.
GiteaMirror commented 2026-04-29 09:51:31 -05:00
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@DaveyBonez commented on GitHub (Apr 6, 2026):

Additional details & troubleshooting already performed (RX 9060 XT - RDNA 4)

Hardware:

  • GPU: AMD Radeon RX 9060 XT 16 GB (RDNA 4 / gfx12xx)
  • OS: Windows 11 Pro 24H2
  • Confirmed working: LM Studio runs Qwen3.5 models perfectly on the exact same hardware with zero errors (using its bundled ROCm stack).

What I already tried:

  • Fresh Ollama install (latest version)
  • Multiple ROCm versions (including 6.4 and 7.1)
  • Hijacked LM Studio’s entire ROCm stack (copied DLLs + set HIP_PATH, PATH, LD_LIBRARY_PATH, etc.) → still got the exact same hipErrorInvalidDeviceFunction (98)
  • Confirmed the error happens during model load / rocBLAS kernel launch (SOLVE_TRI failed)

AMD Support Ticket:
I already provided full diagnostics to AMD Global Customer Care (Ticket #3520556):

  • Complete MSInfo32 (.nfo)
  • DxDiag report
  • Full Ollama error logs showing the hipErrorInvalidDeviceFunction(98)
  • Confirmed the issue has existed since the very first attempt (never worked)

AMD has now asked me to open this GitHub issue so the ROCm team can investigate.

Related issue:
This appears to be the same problem as #14423 (Radeon AI Pro R9700 — also RDNA 4).

Reproduction steps:

  1. Install latest Ollama
  2. ollama run qwen3.5 (or any Qwen3.5 variant)
  3. Immediate 500 error with hipErrorInvalidDeviceFunction (98) + rocBLAS failure

Smaller Qwen3 models and other families may work, but all Qwen3.5 models fail.

Happy to provide any additional logs, run specific tests, or share the full AMD diagnostics files if needed.

Thanks for looking into this — really hoping we can get RDNA 4 consumer cards working properly with Ollama + ROCm.

Additional Context & Deep Troubleshooting (RX 9060 XT - RDNA 4)

Critical observation that may help narrow this down:

  • LM Studio runs Qwen3.5 models perfectly with zero errors on this exact same RX 9060 XT hardware.
  • I went much further and completely hijacked LM Studio’s entire working ROCm stack:
    • Copied all DLLs, libraries, and binaries from LM Studio’s ROCm installation
    • Overrode HIP_PATH, PATH, LD_LIBRARY_PATH, and every relevant environment variable to force Ollama to use LM Studio’s exact ROCm environment
  • Even with LM Studio’s proven-working ROCm stack fully in control, Ollama still immediately fails with the exact same hipErrorInvalidDeviceFunction (98) + SOLVE_TRI failed.

This strongly suggests the problem is not a missing or broken ROCm install, but something specific in how Ollama itself builds/calls the HIP/rocBLAS kernels on RDNA 4 (gfx12xx).

Other details already provided:

  • Issue has existed since the very first attempt (never worked)
  • AMD Support Ticket #3520556 with full MSInfo32 (.nfo), DxDiag, and raw Ollama error logs
  • Related issue: #14423 (same error on Radeon AI Pro R9700 — also RDNA 4)

Reproduction:

  1. Latest Ollama
  2. ollama run qwen3.5 (any size)
  3. Immediate 500 error during model load

Happy to run any specific tests, share the full AMD diagnostics files, or provide whatever else is needed.

Thanks for looking into this.

<!-- gh-comment-id:4189971516 --> @DaveyBonez commented on GitHub (Apr 6, 2026): ### Additional details & troubleshooting already performed (RX 9060 XT - RDNA 4) **Hardware:** - GPU: AMD Radeon RX 9060 XT 16 GB (RDNA 4 / gfx12xx) - OS: Windows 11 Pro 24H2 - Confirmed working: **LM Studio** runs Qwen3.5 models perfectly on the exact same hardware with zero errors (using its bundled ROCm stack). **What I already tried:** - Fresh Ollama install (latest version) - Multiple ROCm versions (including 6.4 and 7.1) - Hijacked LM Studio’s entire ROCm stack (copied DLLs + set `HIP_PATH`, `PATH`, `LD_LIBRARY_PATH`, etc.) → still got the exact same `hipErrorInvalidDeviceFunction (98)` - Confirmed the error happens during model load / rocBLAS kernel launch (`SOLVE_TRI failed`) **AMD Support Ticket:** I already provided full diagnostics to AMD Global Customer Care (Ticket #3520556): - Complete MSInfo32 (.nfo) - DxDiag report - Full Ollama error logs showing the hipErrorInvalidDeviceFunction(98) - Confirmed the issue has existed since the very first attempt (never worked) AMD has now asked me to open this GitHub issue so the ROCm team can investigate. **Related issue:** This appears to be the same problem as #14423 (Radeon AI Pro R9700 — also RDNA 4). **Reproduction steps:** 1. Install latest Ollama 2. `ollama run qwen3.5` (or any Qwen3.5 variant) 3. Immediate 500 error with `hipErrorInvalidDeviceFunction (98)` + rocBLAS failure Smaller Qwen3 models and other families may work, but all Qwen3.5 models fail. Happy to provide any additional logs, run specific tests, or share the full AMD diagnostics files if needed. Thanks for looking into this — really hoping we can get RDNA 4 consumer cards working properly with Ollama + ROCm. ### Additional Context & Deep Troubleshooting (RX 9060 XT - RDNA 4) **Critical observation that may help narrow this down:** - **LM Studio runs Qwen3.5 models perfectly** with zero errors on this exact same RX 9060 XT hardware. - I went **much further** and **completely hijacked LM Studio’s entire working ROCm stack**: - Copied all DLLs, libraries, and binaries from LM Studio’s ROCm installation - Overrode `HIP_PATH`, `PATH`, `LD_LIBRARY_PATH`, and every relevant environment variable to force Ollama to use LM Studio’s exact ROCm environment - Even with LM Studio’s proven-working ROCm stack fully in control, **Ollama still immediately fails** with the exact same `hipErrorInvalidDeviceFunction (98)` + `SOLVE_TRI failed`. This strongly suggests the problem is **not** a missing or broken ROCm install, but something specific in how **Ollama itself** builds/calls the HIP/rocBLAS kernels on RDNA 4 (gfx12xx). **Other details already provided:** - Issue has existed since the very first attempt (never worked) - AMD Support Ticket #3520556 with full MSInfo32 (.nfo), DxDiag, and raw Ollama error logs - Related issue: #14423 (same error on Radeon AI Pro R9700 — also RDNA 4) **Reproduction:** 1. Latest Ollama 2. `ollama run qwen3.5` (any size) 3. Immediate 500 error during model load Happy to run any specific tests, share the full AMD diagnostics files, or provide whatever else is needed. Thanks for looking into this.
GiteaMirror commented 2026-04-29 09:51:32 -05:00
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@ketchup301 commented on GitHub (Apr 6, 2026):

Additional details & troubleshooting already performed (RX 9060 XT - RDNA 4)

Hardware:

  • GPU: AMD Radeon RX 9060 XT 16 GB (RDNA 4 / gfx12xx)
  • OS: Windows 11 Pro 24H2
  • Confirmed working: LM Studio runs Qwen3.5 models perfectly on the exact same hardware with zero errors (using its bundled ROCm stack).

What I already tried:

  • Fresh Ollama install (latest version)
  • Multiple ROCm versions (including 6.4 and 7.1)
  • Hijacked LM Studio’s entire ROCm stack (copied DLLs + set HIP_PATH, PATH, LD_LIBRARY_PATH, etc.) → still got the exact same hipErrorInvalidDeviceFunction (98)
  • Confirmed the error happens during model load / rocBLAS kernel launch (SOLVE_TRI failed)

AMD Support Ticket: I already provided full diagnostics to AMD Global Customer Care (Ticket #3520556):

  • Complete MSInfo32 (.nfo)
  • DxDiag report
  • Full Ollama error logs showing the hipErrorInvalidDeviceFunction(98)
  • Confirmed the issue has existed since the very first attempt (never worked)

AMD has now asked me to open this GitHub issue so the ROCm team can investigate.

Related issue: This appears to be the same problem as #14423 (Radeon AI Pro R9700 — also RDNA 4).

Reproduction steps:

  1. Install latest Ollama
  2. ollama run qwen3.5 (or any Qwen3.5 variant)
  3. Immediate 500 error with hipErrorInvalidDeviceFunction (98) + rocBLAS failure

Smaller Qwen3 models and other families may work, but all Qwen3.5 models fail.

Happy to provide any additional logs, run specific tests, or share the full AMD diagnostics files if needed.

Thanks for looking into this — really hoping we can get RDNA 4 consumer cards working properly with Ollama + ROCm.

Additional Context & Deep Troubleshooting (RX 9060 XT - RDNA 4)

Critical observation that may help narrow this down:

  • LM Studio runs Qwen3.5 models perfectly with zero errors on this exact same RX 9060 XT hardware.

  • I went much further and completely hijacked LM Studio’s entire working ROCm stack:

    • Copied all DLLs, libraries, and binaries from LM Studio’s ROCm installation
    • Overrode HIP_PATH, PATH, LD_LIBRARY_PATH, and every relevant environment variable to force Ollama to use LM Studio’s exact ROCm environment

  • Even with LM Studio’s proven-working ROCm stack fully in control, Ollama still immediately fails with the exact same hipErrorInvalidDeviceFunction (98) + SOLVE_TRI failed.

This strongly suggests the problem is not a missing or broken ROCm install, but something specific in how Ollama itself builds/calls the HIP/rocBLAS kernels on RDNA 4 (gfx12xx).

Other details already provided:

Reproduction:

  1. Latest Ollama
  2. ollama run qwen3.5 (any size)
  3. Immediate 500 error during model load

Happy to run any specific tests, share the full AMD diagnostics files, or provide whatever else is needed.

Thanks for looking into this.

Hey there, I don't know if this helps as I'm not running Windows.
I have an R9700 and an RX9060XT running on a Linux MINT server. Ollama version 0.20.0 and Open-WebUI is my front-end.

+------------------------------------------------------------------------------+
| AMD-SMI 26.2.1+fc0010cf6a    amdgpu version: 6.16.13  ROCm version: 7.2.0    |
| VBIOS version: 00158742                                                      |
| Platform: Linux Baremetal                                                    |
|-------------------------------------+----------------------------------------|
| BDF                        GPU-Name | Mem-Uti   Temp   UEC       Power-Usage |
| GPU  HIP-ID  OAM-ID  Partition-Mode | GFX-Uti    Fan               Mem-Usage |
|=====================================+========================================|
| 0000:04:00.0 ...Radeon AI PRO R9700 | 0 %      80 °C   0            96/300 W |
|   0       0     N/A             N/A | 100 %   36.86           22735/30576 MB |
|-------------------------------------+----------------------------------------|
| 0000:0a:00.0  AMD Radeon RX 9060 XT | 9 %      54 °C   0            53/170 W |
|   1       1     N/A             N/A | 100 %   8.63 %           9536/16304 MB |
+-------------------------------------+----------------------------------------+
+------------------------------------------------------------------------------+
| Processes:                                                                   |
|  GPU        PID  Process Name          GTT_MEM  VRAM_MEM  MEM_USAGE     CU % |
|==============================================================================|
|    0    2468478  N/A                     0.0 B  875.6 MB   875.6 MB  N/A     |
|    0    2471759  N/A                     0.0 B   21.3 GB    21.3 GB  N/A     |
|    1     538998  N/A                     0.0 B    3.9 GB     3.9 GB  N/A     |
|    1    2475517  N/A                     0.0 B    5.3 GB     5.3 GB  N/A     |
+------------------------------------------------------------------------------+

docker exec -it ollama-task ollama ps
NAME ID SIZE PROCESSOR CONTEXT UNTIL
gemma3:4b a2af6cc3eb7f 4.4 GB 100% GPU 4096 Forever
qwen3.5:4b 2a654d98e6fb 5.9 GB 100% GPU 4096 Forever

Logs look like this:

time=2026-04-06T04:25:59.117Z level=INFO source=runner.go:1290 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:40960 KvCacheType: NumThreads:24 GPULayers:63[ID:GPU-89a44a3d58169094 Layers:63(0..62)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-04-06T04:25:59.418Z level=INFO source=runner.go:1290 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:40960 KvCacheType: NumThreads:24 GPULayers:63[ID:GPU-89a44a3d58169094 Layers:63(0..62)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:482 msg="offloading 62 repeating layers to GPU"
time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:489 msg="offloading output layer to GPU"
time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:494 msg="offloaded 63/63 layers to GPU"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:240 msg="model weights" device=ROCm0 size="16.8 GiB"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:245 msg="model weights" device=CPU size="2.6 GiB"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:251 msg="kv cache" device=ROCm0 size="3.7 GiB"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:262 msg="compute graph" device=ROCm0 size="336.9 MiB"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:267 msg="compute graph" device=CPU size="10.5 MiB"
time=2026-04-06T04:25:59.418Z level=INFO source=device.go:272 msg="total memory" size="23.5 GiB"
time=2026-04-06T04:25:59.418Z level=INFO source=sched.go:561 msg="loaded runners" count=2
time=2026-04-06T04:25:59.418Z level=INFO source=server.go:1352 msg="waiting for llama runner to start responding"
time=2026-04-06T04:25:59.434Z level=INFO source=server.go:1386 msg="waiting for server to become available" status="llm server loading model"
time=2026-04-06T04:26:05.207Z level=INFO source=server.go:1390 msg="llama runner started in 6.53 seconds"
[GIN] 2026/04/06 - 04:26:17 | 200 | 19.228768679s |      172.18.0.3 | POST     "/api/chat"
[GIN] 2026/04/06 - 04:27:40 | 404 |       3.646µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:27:40 | 200 |    1.186828ms |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:27:40 | 200 |      52.654µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:27:55 | 200 |   15.835345ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:01 | 200 |   1.18997314s |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   32.577967ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   56.183083ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   84.819279ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   70.117029ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   65.956192ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |   63.341354ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:03 | 200 |  381.289323ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:04 | 200 |  704.155993ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:04 | 200 |  999.753676ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:28:28 | 200 |  24.42472212s |      172.18.0.3 | POST     "/api/chat"
[GIN] 2026/04/06 - 04:29:06 | 200 |   16.700606ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:10 | 200 |  129.557708ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |   30.436158ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |   52.635413ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |   77.593642ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |   66.512537ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |   68.144639ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:11 | 200 |    70.87899ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:12 | 200 |  163.571449ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:12 | 200 |  250.084041ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:12 | 200 |  331.560979ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:29:49 | 200 | 36.894287138s |      172.18.0.3 | POST     "/api/chat"
[GIN] 2026/04/06 - 04:30:36 | 200 |   18.780871ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:41 | 200 |  1.080510191s |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |   32.667153ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |   67.745448ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |   89.376327ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |   89.408368ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |   89.923434ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:43 | 200 |  123.667866ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:44 | 200 |  509.231627ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:44 | 200 |  803.978098ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:30:45 | 200 |  1.163508853s |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:31:17 | 200 | 32.798266191s |      172.18.0.3 | POST     "/api/chat"
[GIN] 2026/04/06 - 04:37:48 | 200 |      70.889µs |       127.0.0.1 | GET      "/api/version"
[GIN] 2026/04/06 - 04:38:13 | 404 |        3.96µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:38:13 | 200 |    1.049572ms |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:38:13 | 200 |      24.328µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:40:38 | 404 |       4.931µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:40:38 | 200 |     446.599µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:40:38 | 200 |      31.753µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:40:41 | 200 |     551.455µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:43:15 | 404 |       2.461µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:43:15 | 200 |     458.133µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:43:15 | 200 |      34.662µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:43:26 | 404 |       4.166µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:43:26 | 200 |     411.701µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:43:26 | 200 |      37.902µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:43:26 | 200 |      50.271µs |      172.18.0.3 | GET      "/api/version"
[GIN] 2026/04/06 - 04:43:38 | 200 |   31.043072ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:43:47 | 200 |      18.454µs |       127.0.0.1 | HEAD     "/"
[GIN] 2026/04/06 - 04:43:47 | 200 |      36.609µs |       127.0.0.1 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:44:20 | 200 |      21.236µs |       127.0.0.1 | HEAD     "/"
[GIN] 2026/04/06 - 04:44:20 | 200 |      32.803µs |       127.0.0.1 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:45:38 | 404 |       5.063µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:45:38 | 200 |     551.786µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:45:38 | 200 |       39.67µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:45:48 | 200 |   35.512711ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:56:15 | 404 |       1.417µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:56:15 | 200 |      447.41µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:56:15 | 200 |      33.815µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:56:29 | 200 |   47.105244ms |      172.18.0.3 | POST     "/api/embed"
[GIN] 2026/04/06 - 04:56:47 | 200 |  17.75208535s |      172.18.0.3 | POST     "/api/chat"
time=2026-04-06T04:58:58.922Z level=ERROR source=server.go:304 msg="llama runner terminated" error="signal: killed"
time=2026-04-06T04:58:59.090Z level=ERROR source=server.go:304 msg="llama runner terminated" error="signal: killed"
time=2026-04-06T04:58:59.348Z level=INFO source=routes.go:1744 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GGML_VK_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES:0 HSA_OVERRIDE_GFX_VERSION:12.0.1 HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:0 OLLAMA_DEBUG:INFO OLLAMA_DEBUG_LOG_REQUESTS:false OLLAMA_EDITOR: OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 OLLAMA_KEEP_ALIVE:2562047h47m16.854775807s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:2 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/root/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NO_CLOUD:false OLLAMA_NUM_PARALLEL:1 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_REMOTES:[ollama.com] OLLAMA_SCHED_SPREAD:false OLLAMA_VULKAN:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]"
time=2026-04-06T04:58:59.348Z level=INFO source=routes.go:1746 msg="Ollama cloud disabled: false"
time=2026-04-06T04:58:59.349Z level=INFO source=images.go:499 msg="total blobs: 26"
time=2026-04-06T04:58:59.349Z level=INFO source=images.go:506 msg="total unused blobs removed: 0"
time=2026-04-06T04:58:59.349Z level=INFO source=routes.go:1802 msg="Listening on [::]:11434 (version 0.20.0)"
time=2026-04-06T04:58:59.350Z level=INFO source=runner.go:67 msg="discovering available GPUs..."
time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:485 msg="user overrode visible devices" HIP_VISIBLE_DEVICES=0
time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:485 msg="user overrode visible devices" HSA_OVERRIDE_GFX_VERSION=12.0.1
time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:489 msg="if GPUs are not correctly discovered, unset and try again"
time=2026-04-06T04:58:59.350Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 40665"
time=2026-04-06T04:58:59.414Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 41195"
time=2026-04-06T04:58:59.556Z level=INFO source=types.go:42 msg="inference compute" id=GPU-89a44a3d58169094 filter_id="" library=ROCm compute=gfx1201 name=ROCm0 description="AMD Radeon Graphics" libdirs=ollama,rocm driver=70226.1 pci_id=0000:04:00.0 type=discrete total="29.9 GiB" available="29.8 GiB"
time=2026-04-06T04:58:59.556Z level=INFO source=routes.go:1852 msg="vram-based default context" total_vram="29.9 GiB" default_num_ctx=32768
[GIN] 2026/04/06 - 04:59:23 | 404 |       4.932µs |      172.18.0.3 | GET      "/models"
[GIN] 2026/04/06 - 04:59:23 | 200 |     550.824µs |      172.18.0.3 | GET      "/api/tags"
[GIN] 2026/04/06 - 04:59:23 | 200 |      68.211µs |      172.18.0.3 | GET      "/api/ps"
[GIN] 2026/04/06 - 04:59:24 | 200 |      64.223µs |      172.18.0.3 | GET      "/api/version"
time=2026-04-06T04:59:39.570Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 41549"
time=2026-04-06T04:59:40.171Z level=WARN source=cpu_linux.go:130 msg="failed to parse CPU allowed micro secs" error="strconv.ParseInt: parsing \"max\": invalid syntax"
time=2026-04-06T04:59:40.178Z level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=8192 n_ctx_train=2048
time=2026-04-06T04:59:40.178Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --model /root/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --port 41235"
time=2026-04-06T04:59:40.179Z level=INFO source=sched.go:484 msg="system memory" total="30.8 GiB" free="30.7 GiB" free_swap="1.1 GiB"
time=2026-04-06T04:59:40.179Z level=INFO source=sched.go:491 msg="gpu memory" id=GPU-89a44a3d58169094 library=ROCm available="29.4 GiB" free="29.8 GiB" minimum="457.0 MiB" overhead="0 B"
time=2026-04-06T04:59:40.179Z level=INFO source=server.go:759 msg="loading model" "model layers"=13 requested=-1
time=2026-04-06T04:59:40.186Z level=INFO source=runner.go:1417 msg="starting ollama engine"
time=2026-04-06T04:59:40.186Z level=INFO source=runner.go:1452 msg="Server listening on 127.0.0.1:41235"
time=2026-04-06T04:59:40.191Z level=INFO source=runner.go:1290 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-04-06T04:59:40.194Z level=INFO source=ggml.go:136 msg="" architecture=nomic-bert file_type=F16 name=nomic-embed-text-v1.5 description="" num_tensors=112 num_key_values=25
load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon Graphics, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: GPU-89a44a3d58169094
load_backend: loaded ROCm backend from /usr/lib/ollama/rocm/libggml-hip.so
time=2026-04-06T04:59:40.244Z level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc)
time=2026-04-06T04:59:40.244Z level=WARN source=runner.go:1219 msg="model does not support caching, setting batch size to context length" batch_size=2048

rocblaslt error: Cannot read "TensileLibrary_lazy_gfx1201.dat": No such file or directory

rocblaslt error: Could not load "TensileLibrary_lazy_gfx1201.dat"
time=2026-04-06T04:59:40.313Z level=INFO source=runner.go:1290 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-04-06T04:59:40.317Z level=WARN source=runner.go:1219 msg="model does not support caching, setting batch size to context length" batch_size=2048
time=2026-04-06T04:59:40.320Z level=INFO source=runner.go:1290 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:482 msg="offloading 12 repeating layers to GPU"
time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:489 msg="offloading output layer to GPU"
time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:494 msg="offloaded 13/13 layers to GPU"
time=2026-04-06T04:59:40.320Z level=INFO source=device.go:240 msg="model weights" device=ROCm0 size="260.9 MiB"
time=2026-04-06T04:59:40.320Z level=INFO source=device.go:245 msg="model weights" device=CPU size="44.7 MiB"
time=2026-04-06T04:59:40.320Z level=INFO source=device.go:262 msg="compute graph" device=ROCm0 size="255.8 MiB"
time=2026-04-06T04:59:40.320Z level=INFO source=device.go:267 msg="compute graph" device=CPU size="6.0 MiB"
time=2026-04-06T04:59:40.320Z level=INFO source=device.go:272 msg="total memory" size="567.3 MiB"
time=2026-04-06T04:59:40.320Z level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-04-06T04:59:40.320Z level=INFO source=server.go:1352 msg="waiting for llama runner to start responding"
time=2026-04-06T04:59:40.324Z level=INFO source=server.go:1386 msg="waiting for server to become available" status="llm server loading model"
time=2026-04-06T04:59:40.576Z level=INFO source=server.go:1390 msg="llama runner started in 0.40 seconds"
[GIN] 2026/04/06 - 04:59:40 | 200 |   1.03633083s |      172.18.0.3 | POST     "/api/embed"

I think the rocblaslt error is because 0.20.0 not having the proper RDNA4 support (been hoping it will be resolved soon), but it's working fine for me. Maybe this helps??? Maybe not.. ?

PS your error reporting is exceptional. I learned a lot by reading it!

<!-- gh-comment-id:4190408432 --> @ketchup301 commented on GitHub (Apr 6, 2026): > ### Additional details & troubleshooting already performed (RX 9060 XT - RDNA 4) > **Hardware:** > > * GPU: AMD Radeon RX 9060 XT 16 GB (RDNA 4 / gfx12xx) > * OS: Windows 11 Pro 24H2 > * Confirmed working: **LM Studio** runs Qwen3.5 models perfectly on the exact same hardware with zero errors (using its bundled ROCm stack). > > **What I already tried:** > > * Fresh Ollama install (latest version) > * Multiple ROCm versions (including 6.4 and 7.1) > * Hijacked LM Studio’s entire ROCm stack (copied DLLs + set `HIP_PATH`, `PATH`, `LD_LIBRARY_PATH`, etc.) → still got the exact same `hipErrorInvalidDeviceFunction (98)` > * Confirmed the error happens during model load / rocBLAS kernel launch (`SOLVE_TRI failed`) > > **AMD Support Ticket:** I already provided full diagnostics to AMD Global Customer Care (Ticket #3520556): > > * Complete MSInfo32 (.nfo) > * DxDiag report > * Full Ollama error logs showing the hipErrorInvalidDeviceFunction(98) > * Confirmed the issue has existed since the very first attempt (never worked) > > AMD has now asked me to open this GitHub issue so the ROCm team can investigate. > > **Related issue:** This appears to be the same problem as [#14423](https://github.com/ollama/ollama/issues/14423) (Radeon AI Pro R9700 — also RDNA 4). > > **Reproduction steps:** > > 1. Install latest Ollama > 2. `ollama run qwen3.5` (or any Qwen3.5 variant) > 3. Immediate 500 error with `hipErrorInvalidDeviceFunction (98)` + rocBLAS failure > > Smaller Qwen3 models and other families may work, but all Qwen3.5 models fail. > > Happy to provide any additional logs, run specific tests, or share the full AMD diagnostics files if needed. > > Thanks for looking into this — really hoping we can get RDNA 4 consumer cards working properly with Ollama + ROCm. > > ### Additional Context & Deep Troubleshooting (RX 9060 XT - RDNA 4) > **Critical observation that may help narrow this down:** > > * **LM Studio runs Qwen3.5 models perfectly** with zero errors on this exact same RX 9060 XT hardware. > * I went **much further** and **completely hijacked LM Studio’s entire working ROCm stack**: > > * Copied all DLLs, libraries, and binaries from LM Studio’s ROCm installation > * Overrode `HIP_PATH`, `PATH`, `LD_LIBRARY_PATH`, and every relevant environment variable to force Ollama to use LM Studio’s exact ROCm environment > * Even with LM Studio’s proven-working ROCm stack fully in control, **Ollama still immediately fails** with the exact same `hipErrorInvalidDeviceFunction (98)` + `SOLVE_TRI failed`. > > This strongly suggests the problem is **not** a missing or broken ROCm install, but something specific in how **Ollama itself** builds/calls the HIP/rocBLAS kernels on RDNA 4 (gfx12xx). > > **Other details already provided:** > > * Issue has existed since the very first attempt (never worked) > * AMD Support Ticket #3520556 with full MSInfo32 (.nfo), DxDiag, and raw Ollama error logs > * Related issue: [[qwen3.5 local models] Error: 500 Internal Server Error on AMD Radeon AI Pro R9700 (ROCm error: invalid device function, SOLVE_TRI failed) #14423](https://github.com/ollama/ollama/issues/14423) (same error on Radeon AI Pro R9700 — also RDNA 4) > > **Reproduction:** > > 1. Latest Ollama > 2. `ollama run qwen3.5` (any size) > 3. Immediate 500 error during model load > > Happy to run any specific tests, share the full AMD diagnostics files, or provide whatever else is needed. > > Thanks for looking into this. Hey there, I don't know if this helps as I'm not running Windows. I have an R9700 and an RX9060XT running on a Linux MINT server. Ollama version 0.20.0 and Open-WebUI is my front-end. ``` +------------------------------------------------------------------------------+ | AMD-SMI 26.2.1+fc0010cf6a amdgpu version: 6.16.13 ROCm version: 7.2.0 | | VBIOS version: 00158742 | | Platform: Linux Baremetal | |-------------------------------------+----------------------------------------| | BDF GPU-Name | Mem-Uti Temp UEC Power-Usage | | GPU HIP-ID OAM-ID Partition-Mode | GFX-Uti Fan Mem-Usage | |=====================================+========================================| | 0000:04:00.0 ...Radeon AI PRO R9700 | 0 % 80 °C 0 96/300 W | | 0 0 N/A N/A | 100 % 36.86 22735/30576 MB | |-------------------------------------+----------------------------------------| | 0000:0a:00.0 AMD Radeon RX 9060 XT | 9 % 54 °C 0 53/170 W | | 1 1 N/A N/A | 100 % 8.63 % 9536/16304 MB | +-------------------------------------+----------------------------------------+ +------------------------------------------------------------------------------+ | Processes: | | GPU PID Process Name GTT_MEM VRAM_MEM MEM_USAGE CU % | |==============================================================================| | 0 2468478 N/A 0.0 B 875.6 MB 875.6 MB N/A | | 0 2471759 N/A 0.0 B 21.3 GB 21.3 GB N/A | | 1 538998 N/A 0.0 B 3.9 GB 3.9 GB N/A | | 1 2475517 N/A 0.0 B 5.3 GB 5.3 GB N/A | +------------------------------------------------------------------------------+ ``` docker exec -it ollama-task ollama ps NAME ID SIZE PROCESSOR CONTEXT UNTIL gemma3:4b a2af6cc3eb7f 4.4 GB 100% GPU 4096 Forever qwen3.5:4b 2a654d98e6fb 5.9 GB 100% GPU 4096 Forever Logs look like this: ``` time=2026-04-06T04:25:59.117Z level=INFO source=runner.go:1290 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:40960 KvCacheType: NumThreads:24 GPULayers:63[ID:GPU-89a44a3d58169094 Layers:63(0..62)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-04-06T04:25:59.418Z level=INFO source=runner.go:1290 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:40960 KvCacheType: NumThreads:24 GPULayers:63[ID:GPU-89a44a3d58169094 Layers:63(0..62)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:482 msg="offloading 62 repeating layers to GPU" time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:489 msg="offloading output layer to GPU" time=2026-04-06T04:25:59.418Z level=INFO source=ggml.go:494 msg="offloaded 63/63 layers to GPU" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:240 msg="model weights" device=ROCm0 size="16.8 GiB" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:245 msg="model weights" device=CPU size="2.6 GiB" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:251 msg="kv cache" device=ROCm0 size="3.7 GiB" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:262 msg="compute graph" device=ROCm0 size="336.9 MiB" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:267 msg="compute graph" device=CPU size="10.5 MiB" time=2026-04-06T04:25:59.418Z level=INFO source=device.go:272 msg="total memory" size="23.5 GiB" time=2026-04-06T04:25:59.418Z level=INFO source=sched.go:561 msg="loaded runners" count=2 time=2026-04-06T04:25:59.418Z level=INFO source=server.go:1352 msg="waiting for llama runner to start responding" time=2026-04-06T04:25:59.434Z level=INFO source=server.go:1386 msg="waiting for server to become available" status="llm server loading model" time=2026-04-06T04:26:05.207Z level=INFO source=server.go:1390 msg="llama runner started in 6.53 seconds" [GIN] 2026/04/06 - 04:26:17 | 200 | 19.228768679s | 172.18.0.3 | POST "/api/chat" [GIN] 2026/04/06 - 04:27:40 | 404 | 3.646µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:27:40 | 200 | 1.186828ms | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:27:40 | 200 | 52.654µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:27:55 | 200 | 15.835345ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:01 | 200 | 1.18997314s | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 32.577967ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 56.183083ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 84.819279ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 70.117029ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 65.956192ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 63.341354ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:03 | 200 | 381.289323ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:04 | 200 | 704.155993ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:04 | 200 | 999.753676ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:28:28 | 200 | 24.42472212s | 172.18.0.3 | POST "/api/chat" [GIN] 2026/04/06 - 04:29:06 | 200 | 16.700606ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:10 | 200 | 129.557708ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 30.436158ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 52.635413ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 77.593642ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 66.512537ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 68.144639ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:11 | 200 | 70.87899ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:12 | 200 | 163.571449ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:12 | 200 | 250.084041ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:12 | 200 | 331.560979ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:29:49 | 200 | 36.894287138s | 172.18.0.3 | POST "/api/chat" [GIN] 2026/04/06 - 04:30:36 | 200 | 18.780871ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:41 | 200 | 1.080510191s | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 32.667153ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 67.745448ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 89.376327ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 89.408368ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 89.923434ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:43 | 200 | 123.667866ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:44 | 200 | 509.231627ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:44 | 200 | 803.978098ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:30:45 | 200 | 1.163508853s | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:31:17 | 200 | 32.798266191s | 172.18.0.3 | POST "/api/chat" [GIN] 2026/04/06 - 04:37:48 | 200 | 70.889µs | 127.0.0.1 | GET "/api/version" [GIN] 2026/04/06 - 04:38:13 | 404 | 3.96µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:38:13 | 200 | 1.049572ms | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:38:13 | 200 | 24.328µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:40:38 | 404 | 4.931µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:40:38 | 200 | 446.599µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:40:38 | 200 | 31.753µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:40:41 | 200 | 551.455µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:43:15 | 404 | 2.461µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:43:15 | 200 | 458.133µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:43:15 | 200 | 34.662µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:43:26 | 404 | 4.166µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:43:26 | 200 | 411.701µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:43:26 | 200 | 37.902µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:43:26 | 200 | 50.271µs | 172.18.0.3 | GET "/api/version" [GIN] 2026/04/06 - 04:43:38 | 200 | 31.043072ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:43:47 | 200 | 18.454µs | 127.0.0.1 | HEAD "/" [GIN] 2026/04/06 - 04:43:47 | 200 | 36.609µs | 127.0.0.1 | GET "/api/ps" [GIN] 2026/04/06 - 04:44:20 | 200 | 21.236µs | 127.0.0.1 | HEAD "/" [GIN] 2026/04/06 - 04:44:20 | 200 | 32.803µs | 127.0.0.1 | GET "/api/ps" [GIN] 2026/04/06 - 04:45:38 | 404 | 5.063µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:45:38 | 200 | 551.786µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:45:38 | 200 | 39.67µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:45:48 | 200 | 35.512711ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:56:15 | 404 | 1.417µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:56:15 | 200 | 447.41µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:56:15 | 200 | 33.815µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:56:29 | 200 | 47.105244ms | 172.18.0.3 | POST "/api/embed" [GIN] 2026/04/06 - 04:56:47 | 200 | 17.75208535s | 172.18.0.3 | POST "/api/chat" time=2026-04-06T04:58:58.922Z level=ERROR source=server.go:304 msg="llama runner terminated" error="signal: killed" time=2026-04-06T04:58:59.090Z level=ERROR source=server.go:304 msg="llama runner terminated" error="signal: killed" time=2026-04-06T04:58:59.348Z level=INFO source=routes.go:1744 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GGML_VK_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES:0 HSA_OVERRIDE_GFX_VERSION:12.0.1 HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:0 OLLAMA_DEBUG:INFO OLLAMA_DEBUG_LOG_REQUESTS:false OLLAMA_EDITOR: OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 OLLAMA_KEEP_ALIVE:2562047h47m16.854775807s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:2 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/root/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NO_CLOUD:false OLLAMA_NUM_PARALLEL:1 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_REMOTES:[ollama.com] OLLAMA_SCHED_SPREAD:false OLLAMA_VULKAN:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]" time=2026-04-06T04:58:59.348Z level=INFO source=routes.go:1746 msg="Ollama cloud disabled: false" time=2026-04-06T04:58:59.349Z level=INFO source=images.go:499 msg="total blobs: 26" time=2026-04-06T04:58:59.349Z level=INFO source=images.go:506 msg="total unused blobs removed: 0" time=2026-04-06T04:58:59.349Z level=INFO source=routes.go:1802 msg="Listening on [::]:11434 (version 0.20.0)" time=2026-04-06T04:58:59.350Z level=INFO source=runner.go:67 msg="discovering available GPUs..." time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:485 msg="user overrode visible devices" HIP_VISIBLE_DEVICES=0 time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:485 msg="user overrode visible devices" HSA_OVERRIDE_GFX_VERSION=12.0.1 time=2026-04-06T04:58:59.350Z level=WARN source=runner.go:489 msg="if GPUs are not correctly discovered, unset and try again" time=2026-04-06T04:58:59.350Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 40665" time=2026-04-06T04:58:59.414Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 41195" time=2026-04-06T04:58:59.556Z level=INFO source=types.go:42 msg="inference compute" id=GPU-89a44a3d58169094 filter_id="" library=ROCm compute=gfx1201 name=ROCm0 description="AMD Radeon Graphics" libdirs=ollama,rocm driver=70226.1 pci_id=0000:04:00.0 type=discrete total="29.9 GiB" available="29.8 GiB" time=2026-04-06T04:58:59.556Z level=INFO source=routes.go:1852 msg="vram-based default context" total_vram="29.9 GiB" default_num_ctx=32768 [GIN] 2026/04/06 - 04:59:23 | 404 | 4.932µs | 172.18.0.3 | GET "/models" [GIN] 2026/04/06 - 04:59:23 | 200 | 550.824µs | 172.18.0.3 | GET "/api/tags" [GIN] 2026/04/06 - 04:59:23 | 200 | 68.211µs | 172.18.0.3 | GET "/api/ps" [GIN] 2026/04/06 - 04:59:24 | 200 | 64.223µs | 172.18.0.3 | GET "/api/version" time=2026-04-06T04:59:39.570Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --port 41549" time=2026-04-06T04:59:40.171Z level=WARN source=cpu_linux.go:130 msg="failed to parse CPU allowed micro secs" error="strconv.ParseInt: parsing \"max\": invalid syntax" time=2026-04-06T04:59:40.178Z level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=8192 n_ctx_train=2048 time=2026-04-06T04:59:40.178Z level=INFO source=server.go:432 msg="starting runner" cmd="/usr/bin/ollama runner --ollama-engine --model /root/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --port 41235" time=2026-04-06T04:59:40.179Z level=INFO source=sched.go:484 msg="system memory" total="30.8 GiB" free="30.7 GiB" free_swap="1.1 GiB" time=2026-04-06T04:59:40.179Z level=INFO source=sched.go:491 msg="gpu memory" id=GPU-89a44a3d58169094 library=ROCm available="29.4 GiB" free="29.8 GiB" minimum="457.0 MiB" overhead="0 B" time=2026-04-06T04:59:40.179Z level=INFO source=server.go:759 msg="loading model" "model layers"=13 requested=-1 time=2026-04-06T04:59:40.186Z level=INFO source=runner.go:1417 msg="starting ollama engine" time=2026-04-06T04:59:40.186Z level=INFO source=runner.go:1452 msg="Server listening on 127.0.0.1:41235" time=2026-04-06T04:59:40.191Z level=INFO source=runner.go:1290 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-04-06T04:59:40.194Z level=INFO source=ggml.go:136 msg="" architecture=nomic-bert file_type=F16 name=nomic-embed-text-v1.5 description="" num_tensors=112 num_key_values=25 load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon Graphics, gfx1201 (0x1201), VMM: no, Wave Size: 32, ID: GPU-89a44a3d58169094 load_backend: loaded ROCm backend from /usr/lib/ollama/rocm/libggml-hip.so time=2026-04-06T04:59:40.244Z level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc) time=2026-04-06T04:59:40.244Z level=WARN source=runner.go:1219 msg="model does not support caching, setting batch size to context length" batch_size=2048 rocblaslt error: Cannot read "TensileLibrary_lazy_gfx1201.dat": No such file or directory rocblaslt error: Could not load "TensileLibrary_lazy_gfx1201.dat" time=2026-04-06T04:59:40.313Z level=INFO source=runner.go:1290 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-04-06T04:59:40.317Z level=WARN source=runner.go:1219 msg="model does not support caching, setting batch size to context length" batch_size=2048 time=2026-04-06T04:59:40.320Z level=INFO source=runner.go:1290 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Disabled KvSize:2048 KvCacheType: NumThreads:24 GPULayers:13[ID:GPU-89a44a3d58169094 Layers:13(0..12)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:482 msg="offloading 12 repeating layers to GPU" time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:489 msg="offloading output layer to GPU" time=2026-04-06T04:59:40.320Z level=INFO source=ggml.go:494 msg="offloaded 13/13 layers to GPU" time=2026-04-06T04:59:40.320Z level=INFO source=device.go:240 msg="model weights" device=ROCm0 size="260.9 MiB" time=2026-04-06T04:59:40.320Z level=INFO source=device.go:245 msg="model weights" device=CPU size="44.7 MiB" time=2026-04-06T04:59:40.320Z level=INFO source=device.go:262 msg="compute graph" device=ROCm0 size="255.8 MiB" time=2026-04-06T04:59:40.320Z level=INFO source=device.go:267 msg="compute graph" device=CPU size="6.0 MiB" time=2026-04-06T04:59:40.320Z level=INFO source=device.go:272 msg="total memory" size="567.3 MiB" time=2026-04-06T04:59:40.320Z level=INFO source=sched.go:561 msg="loaded runners" count=1 time=2026-04-06T04:59:40.320Z level=INFO source=server.go:1352 msg="waiting for llama runner to start responding" time=2026-04-06T04:59:40.324Z level=INFO source=server.go:1386 msg="waiting for server to become available" status="llm server loading model" time=2026-04-06T04:59:40.576Z level=INFO source=server.go:1390 msg="llama runner started in 0.40 seconds" [GIN] 2026/04/06 - 04:59:40 | 200 | 1.03633083s | 172.18.0.3 | POST "/api/embed" ``` I think the rocblaslt error is because 0.20.0 not having the proper RDNA4 support (been hoping it will be resolved soon), but it's working fine for me. Maybe this helps??? Maybe not.. ? PS your error reporting is exceptional. I learned a lot by reading it!
GiteaMirror commented 2026-04-29 09:51:34 -05:00
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@DaveyBonez commented on GitHub (Apr 6, 2026):

What don't you see?
`PS C:\Users\DaveyBoneZ\AppData\Local\Programs\Ollama\lib\ollama\rocm\rocblas\library> ls

Directory: C:\Users\DaveyBoneZ\AppData\Local\Programs\Ollama\lib\ollama\rocm\rocblas\library

Mode LastWriteTime Length Name

-a--- 4/4/2026 5:43 AM 248288 Kernels.so-000-gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 262120 Kernels.so-000-gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 262376 Kernels.so-000-gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 262120 Kernels.so-000-gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 260840 Kernels.so-000-gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 243168 Kernels.so-000-gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 23026 TensileLibrary_lazy_gfx1030.dat
-a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1100.dat
-a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1101.dat
-a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1102.dat
-a--- 4/4/2026 5:43 AM 17653 TensileLibrary_lazy_gfx1151.dat
-a--- 4/4/2026 5:43 AM 31798 TensileLibrary_lazy_gfx906.dat
-a--- 4/4/2026 5:43 AM 161304 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 170784 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 155672 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 43504 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 87560 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 687504 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx906.co
-a--- 4/4/2026 5:43 AM 127116 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx906.dat
-a--- 4/4/2026 5:43 AM 134320 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 141240 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 141240 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 142264 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 141240 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 130224 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 37230 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 28000 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 1936432 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx906.co
-a--- 4/4/2026 5:43 AM 249900 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx906.dat
-a--- 4/4/2026 5:43 AM 161048 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 170016 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 169760 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 169760 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 155416 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 43848 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 90680 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 1058104 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_gfx906.co
-a--- 4/4/2026 5:43 AM 164390 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_gfx906.dat
-a--- 4/4/2026 5:43 AM 133808 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 141496 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 141496 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 141752 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 141496 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 129968 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 37398 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 112296 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 1320704 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_gfx906.co
-a--- 4/4/2026 5:43 AM 205208 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Alik_Bljk_Cijk_Dijk_gfx906.dat
-a--- 4/4/2026 5:43 AM 474768 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 500376 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 500376 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 500632 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 500376 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 461456 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 56121 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 16798632 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1100.co
-a--- 4/4/2026 5:43 AM 549603 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1100.dat
-a--- 4/4/2026 5:43 AM 17275880 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1101.co
-a--- 4/4/2026 5:43 AM 583354 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1101.dat
-a--- 4/4/2026 5:43 AM 11487568 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1102.co
-a--- 4/4/2026 5:43 AM 244064 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_gfx1102.dat
-a--- 4/4/2026 5:43 AM 437856 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 469864 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 469864 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 472168 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 469864 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx1151.hsaco
-a--- 4/4/2026 5:43 AM 430176 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco
-a--- 4/4/2026 5:43 AM 53167 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_fallback.dat
-a--- 4/4/2026 5:43 AM 16199336 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1100.co
-a--- 4/4/2026 5:43 AM 645565 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1100.dat
-a--- 4/4/2026 5:43 AM 6410600 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1101.co
-a--- 4/4/2026 5:43 AM 309377 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1101.dat
-a--- 4/4/2026 5:43 AM 8035592 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1102.co
-a--- 4/4/2026 5:43 AM 215028 TensileLibrary_Type_BB_HPA_Contraction_l_Ailk_Bljk_Cijk_Dijk_gfx1102.dat
-a--- 4/4/2026 5:43 AM 189456 TensileLibrary_Type_BB_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1030.hsaco
-a--- 4/4/2026 5:43 AM 199448 TensileLibrary_Type_BB_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1100.hsaco
-a--- 4/4/2026 5:43 AM 199448 TensileLibrary_Type_BB_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1101.hsaco
-a--- 4/4/2026 5:43 AM 198936 TensileLibrary_Type_BB_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1102.hsaco
-a--- 4/4/2026 5:43 AM 198424 TensileLibrary_Type_BB_HPA_Contraction_l_Alik_Bjlk_Cijk_Dijk_fallback_gfx1151.hsaco
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-a--- 4/4/2026 5:43 AM 115291 TensileManifest.txt

PS C:\Users\DaveyBoneZ\AppData\Local\Programs\Ollama\lib\ollama\rocm\rocblas\library>`

<!-- gh-comment-id:4193762973 --> @DaveyBonez commented on GitHub (Apr 6, 2026): What don't you see? `PS C:\Users\DaveyBoneZ\AppData\Local\Programs\Ollama\lib\ollama\rocm\rocblas\library> ls Directory: C:\Users\DaveyBoneZ\AppData\Local\Programs\Ollama\lib\ollama\rocm\rocblas\library Mode LastWriteTime Length Name ---- ------------- ------ ---- -a--- 4/4/2026 5:43 AM 248288 Kernels.so-000-gfx1030.hsaco -a--- 4/4/2026 5:43 AM 262120 Kernels.so-000-gfx1100.hsaco -a--- 4/4/2026 5:43 AM 262376 Kernels.so-000-gfx1101.hsaco -a--- 4/4/2026 5:43 AM 262120 Kernels.so-000-gfx1102.hsaco -a--- 4/4/2026 5:43 AM 260840 Kernels.so-000-gfx1151.hsaco -a--- 4/4/2026 5:43 AM 243168 Kernels.so-000-gfx906-xnack-.hsaco -a--- 4/4/2026 5:43 AM 23026 TensileLibrary_lazy_gfx1030.dat -a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1100.dat -a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1101.dat -a--- 4/4/2026 5:43 AM 24186 TensileLibrary_lazy_gfx1102.dat -a--- 4/4/2026 5:43 AM 17653 TensileLibrary_lazy_gfx1151.dat -a--- 4/4/2026 5:43 AM 31798 TensileLibrary_lazy_gfx906.dat -a--- 4/4/2026 5:43 AM 161304 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1030.hsaco -a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1100.hsaco -a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1101.hsaco -a--- 4/4/2026 5:43 AM 170784 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1102.hsaco -a--- 4/4/2026 5:43 AM 170272 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx1151.hsaco -a--- 4/4/2026 5:43 AM 155672 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback_gfx906-xnack-.hsaco -a--- 4/4/2026 5:43 AM 43504 TensileLibrary_Type_4xi8I_HPA_Contraction_l_Ailk_Bjlk_Cijk_Dijk_fallback.dat -a--- 4/4/2026 5:43 AM 87560 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GiteaMirror commented 2026-04-29 09:51:35 -05:00
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@DaveyBonez commented on GitHub (Apr 6, 2026):

So since it is not in their backend it takes it from your installed rocm. My bet since it will run other models is that the Ollama backend that is using your rocm drivers is not fully matured enough to use the functions. Or there is an error in the rocm driver that LMStudio patched in their back end.
But I'm not going to hold my breath since this error has been reported since late February.

<!-- gh-comment-id:4193817706 --> @DaveyBonez commented on GitHub (Apr 6, 2026): So since it is not in their backend it takes it from your installed rocm. My bet since it will run other models is that the Ollama backend that is using your rocm drivers is not fully matured enough to use the functions. Or there is an error in the rocm driver that LMStudio patched in their back end. But I'm not going to hold my breath since this error has been reported since late February.
GiteaMirror commented 2026-04-29 09:51:36 -05:00
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@DaveyBonez commented on GitHub (Apr 9, 2026):

https://github.com/ROCm/ROCm/issues/6120#issuecomment-4216175584

tcgu-amd
13 minutes ago · edited by tcgu-amd
Hi @DaveyBonez thanks for the clarifications. As you said, Ollama’s own rocBLAS library only contains kernels for gfx1030 / gfx1100–gfx1151 / gfx906. No gfx1200 or gfx1201 files at all., which suggests that hipErrorInvalidDeviceFunction is triggered due to missing modules. In other words, Ollama was not built with gfx12 support on Windows. I checked out Ollama docs https://docs.ollama.com/gpu#windows-support, and it does indeed seem to suggest that Ollama on windows is still stuck on ROCm 6.1 and does not suport gfx12. In anycase, it seems to be more appropriate to raise this on the Ollama side.

<!-- gh-comment-id:4216256534 --> @DaveyBonez commented on GitHub (Apr 9, 2026): https://github.com/ROCm/ROCm/issues/6120#issuecomment-4216175584 tcgu-amd 13 minutes ago · edited by tcgu-amd Hi @DaveyBonez thanks for the clarifications. As you said, Ollama’s own rocBLAS library only contains kernels for gfx1030 / gfx1100–gfx1151 / gfx906. No gfx1200 or gfx1201 files at all., which suggests that hipErrorInvalidDeviceFunction is triggered due to missing modules. In other words, Ollama was not built with gfx12 support on Windows. I checked out Ollama docs https://docs.ollama.com/gpu#windows-support, and it does indeed seem to suggest that Ollama on windows is still stuck on ROCm 6.1 and does not suport gfx12. In anycase, it seems to be more appropriate to raise this on the Ollama side.
GiteaMirror commented 2026-04-29 09:51:37 -05:00
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@solitario001 commented on GitHub (Apr 24, 2026):

It's not working on RDNA 4. I've tested it here using two GPUs (RX 9060 XT 16GB & RX 9070 XT 16GB) and it throws the same error even when isolating a single GPU. I'm running on Linux Mint.

Image
<!-- gh-comment-id:4309855070 --> @solitario001 commented on GitHub (Apr 24, 2026): It's not working on RDNA 4. I've tested it here using two GPUs (RX 9060 XT 16GB & RX 9070 XT 16GB) and it throws the same error even when isolating a single GPU. I'm running on Linux Mint. <img width="2694" height="956" alt="Image" src="https://github.com/user-attachments/assets/6af6c758-930c-4086-87ac-e43e0ca434d5" />
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