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[GH-ISSUE #9771] Windows 11 Ollama 0.6.1 ROCm on gfx1151 is broken #9553 #32149

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opened 2026-04-22 13:07:05 -05:00 by GiteaMirror · 1 comment
GiteaMirror commented 2026-04-22 13:07:05 -05:00
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Originally created by @zztop007 on GitHub (Mar 14, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9771

What is the issue?

#9553

Relevant log output

ollama-windows-amd64>ollama.exe serve
2025/03/14 19:06:50 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\donda\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 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_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-03-14T19:06:50.529+01:00 level=INFO source=images.go:432 msg="total blobs: 22"
time=2025-03-14T19:06:50.530+01:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0"
time=2025-03-14T19:06:50.531+01:00 level=INFO source=routes.go:1297 msg="Listening on 127.0.0.1:11434 (version 0.6.1-rc0)"
time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32
time=2025-03-14T19:06:52.150+01:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=rocm variant="" compute=gfx1151 driver=6.3 name="AMD Radeon(TM) 8060S Graphics" total="16.9 GiB" available="16.7 GiB"
[GIN] 2025/03/14 - 19:07:00 | 200 |     41.5922ms |       127.0.0.1 | GET      "/api/tags"
[GIN] 2025/03/14 - 19:07:00 | 200 |      2.2299ms |       127.0.0.1 | GET      "/api/tags"
[GIN] 2025/03/14 - 19:07:07 | 200 |      2.0741ms |       127.0.0.1 | GET      "/api/tags"
[GIN] 2025/03/14 - 19:07:07 | 200 |      1.4182ms |       127.0.0.1 | GET      "/api/tags"
[GIN] 2025/03/14 - 19:07:20 | 200 |       3.052ms |       127.0.0.1 | GET      "/api/tags"
[GIN] 2025/03/14 - 19:07:20 | 200 |            0s |       127.0.0.1 | GET      "/"
[GIN] 2025/03/14 - 19:07:20 | 200 |      1.0169ms |       127.0.0.1 | GET      "/api/tags"
time=2025-03-14T19:07:31.281+01:00 level=INFO source=sched.go:186 msg="one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency"
time=2025-03-14T19:07:31.300+01:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0
time=2025-03-14T19:07:31.300+01:00 level=INFO source=sched.go:715 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 gpu=0 parallel=4 available=17779961856 required="2.5 GiB"
time=2025-03-14T19:07:31.669+01:00 level=INFO source=server.go:105 msg="system memory" total="23.6 GiB" free="13.1 GiB" free_swap="9.4 GiB"
time=2025-03-14T19:07:31.671+01:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0
time=2025-03-14T19:07:31.671+01:00 level=INFO source=server.go:138 msg=offload library=rocm layers.requested=-1 layers.model=17 layers.offload=17 layers.split="" memory.available="[16.6 GiB]" memory.gpu_overhead="0 B" memory.required.full="2.5 GiB" memory.required.partial="2.5 GiB" memory.required.kv="256.0 MiB" memory.required.allocations="[2.5 GiB]" memory.weights.total="986.2 MiB" memory.weights.repeating="986.2 MiB" memory.weights.nonrepeating="266.2 MiB" memory.graph.full="544.0 MiB" memory.graph.partial="554.3 MiB"
llama_model_loader: loaded meta data with 30 key-value pairs and 147 tensors from C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 (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              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Llama 3.2 1B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Llama-3.2
llama_model_loader: - kv   5:                         general.size_label str              = 1B
llama_model_loader: - kv   6:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   7:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   8:                          llama.block_count u32              = 16
llama_model_loader: - kv   9:                       llama.context_length u32              = 131072
llama_model_loader: - kv  10:                     llama.embedding_length u32              = 2048
llama_model_loader: - kv  11:                  llama.feed_forward_length u32              = 8192
llama_model_loader: - kv  12:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv  13:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  15:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  16:                 llama.attention.key_length u32              = 64
llama_model_loader: - kv  17:               llama.attention.value_length u32              = 64
llama_model_loader: - kv  18:                          general.file_type u32              = 7
llama_model_loader: - kv  19:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  20:                 llama.rope.dimension_count u32              = 64
llama_model_loader: - kv  21:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  22:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  23:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  24:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  25:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  27:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  29:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   34 tensors
llama_model_loader: - type q8_0:  113 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 1.22 GiB (8.50 BPW)
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch             = llama
print_info: vocab_only       = 1
print_info: model type       = ?B
print_info: model params     = 1.24 B
print_info: general.name     = Llama 3.2 1B Instruct
print_info: vocab type       = BPE
print_info: n_vocab          = 128256
print_info: n_merges         = 280147
print_info: BOS token        = 128000 '<|begin_of_text|>'
print_info: EOS token        = 128009 '<|eot_id|>'
print_info: EOT token        = 128009 '<|eot_id|>'
print_info: EOM token        = 128008 '<|eom_id|>'
print_info: LF token         = 198 'Ċ'
print_info: EOG token        = 128008 '<|eom_id|>'
print_info: EOG token        = 128009 '<|eot_id|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2025-03-14T19:07:31.833+01:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\donda\\Downloads\\ollama-windows-amd64\\ollama.exe runner --model C:\\Users\\donda\\.ollama\\models\\blobs\\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 --ctx-size 8192 --batch-size 512 --n-gpu-layers 17 --threads 16 --parallel 4 --port 55568"
time=2025-03-14T19:07:31.837+01:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-14T19:07:31.838+01:00 level=INFO source=server.go:585 msg="waiting for llama runner to start responding"
time=2025-03-14T19:07:31.839+01:00 level=INFO source=server.go:619 msg="waiting for server to become available" status="llm server error"
time=2025-03-14T19:07:31.866+01:00 level=INFO source=runner.go:931 msg="starting go runner"
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(TM) 8060S Graphics, gfx1151 (0x1151), VMM: no, Wave Size: 32
load_backend: loaded ROCm backend from C:\Users\donda\Downloads\ollama-windows-amd64\lib\ollama\rocm\ggml-hip.dll
load_backend: loaded CPU backend from C:\Users\donda\Downloads\ollama-windows-amd64\lib\ollama\ggml-cpu-icelake.dll
time=2025-03-14T19:08:06.787+01:00 level=INFO source=ggml.go:109 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.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)
time=2025-03-14T19:08:06.788+01:00 level=INFO source=runner.go:991 msg="Server listening on 127.0.0.1:55568"
time=2025-03-14T19:08:06.972+01:00 level=INFO source=server.go:619 msg="waiting for server to become available" status="llm server loading model"
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon(TM) 8060S Graphics) - 17112 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 147 tensors from C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 (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              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Llama 3.2 1B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Llama-3.2
llama_model_loader: - kv   5:                         general.size_label str              = 1B
llama_model_loader: - kv   6:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   7:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   8:                          llama.block_count u32              = 16
llama_model_loader: - kv   9:                       llama.context_length u32              = 131072
llama_model_loader: - kv  10:                     llama.embedding_length u32              = 2048
llama_model_loader: - kv  11:                  llama.feed_forward_length u32              = 8192
llama_model_loader: - kv  12:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv  13:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  15:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  16:                 llama.attention.key_length u32              = 64
llama_model_loader: - kv  17:               llama.attention.value_length u32              = 64
llama_model_loader: - kv  18:                          general.file_type u32              = 7
llama_model_loader: - kv  19:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  20:                 llama.rope.dimension_count u32              = 64
llama_model_loader: - kv  21:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  22:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  23:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  24:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  25:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  27:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  29:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   34 tensors
llama_model_loader: - type q8_0:  113 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 1.22 GiB (8.50 BPW)
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 131072
print_info: n_embd           = 2048
print_info: n_layer          = 16
print_info: n_head           = 32
print_info: n_head_kv        = 8
print_info: n_rot            = 64
print_info: n_swa            = 0
print_info: n_embd_head_k    = 64
print_info: n_embd_head_v    = 64
print_info: n_gqa            = 4
print_info: n_embd_k_gqa     = 512
print_info: n_embd_v_gqa     = 512
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: n_ff             = 8192
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 131072
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 1B
print_info: model params     = 1.24 B
print_info: general.name     = Llama 3.2 1B Instruct
print_info: vocab type       = BPE
print_info: n_vocab          = 128256
print_info: n_merges         = 280147
print_info: BOS token        = 128000 '<|begin_of_text|>'
print_info: EOS token        = 128009 '<|eot_id|>'
print_info: EOT token        = 128009 '<|eot_id|>'
print_info: EOM token        = 128008 '<|eom_id|>'
print_info: LF token         = 198 'Ċ'
print_info: EOG token        = 128008 '<|eom_id|>'
print_info: EOG token        = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 16 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 17/17 layers to GPU
load_tensors:        ROCm0 model buffer size =  1252.41 MiB
load_tensors:   CPU_Mapped model buffer size =   266.16 MiB
llama_init_from_model: n_seq_max     = 4
llama_init_from_model: n_ctx         = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch       = 2048
llama_init_from_model: n_ubatch      = 512
llama_init_from_model: flash_attn    = 0
llama_init_from_model: freq_base     = 500000.0
llama_init_from_model: freq_scale    = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 16, can_shift = 1
llama_kv_cache_init:      ROCm0 KV buffer size =   256.00 MiB
llama_init_from_model: KV self size  =  256.00 MiB, K (f16):  128.00 MiB, V (f16):  128.00 MiB
llama_init_from_model:  ROCm_Host  output buffer size =     1.99 MiB
llama_init_from_model:      ROCm0 compute buffer size =   544.00 MiB
llama_init_from_model:  ROCm_Host compute buffer size =    20.01 MiB
llama_init_from_model: graph nodes  = 518
llama_init_from_model: graph splits = 2
time=2025-03-14T19:08:08.725+01:00 level=INFO source=server.go:624 msg="llama runner started in 36.89 seconds"
ggml_cuda_compute_forward: RMS_NORM 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:2315
  err
C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:73: ROCm error
[GIN] 2025/03/14 - 19:08:08 | 200 |   37.8614692s |       127.0.0.1 | POST     "/api/chat"
time=2025-03-14T19:08:08.931+01:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"

OS

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GPU

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CPU

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Ollama version

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Originally created by @zztop007 on GitHub (Mar 14, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9771 ### What is the issue? #9553 ### Relevant log output ```shell ollama-windows-amd64>ollama.exe serve 2025/03/14 19:06:50 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\donda\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 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_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-03-14T19:06:50.529+01:00 level=INFO source=images.go:432 msg="total blobs: 22" time=2025-03-14T19:06:50.530+01:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0" time=2025-03-14T19:06:50.531+01:00 level=INFO source=routes.go:1297 msg="Listening on 127.0.0.1:11434 (version 0.6.1-rc0)" time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-03-14T19:06:50.531+01:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32 time=2025-03-14T19:06:52.150+01:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=rocm variant="" compute=gfx1151 driver=6.3 name="AMD Radeon(TM) 8060S Graphics" total="16.9 GiB" available="16.7 GiB" [GIN] 2025/03/14 - 19:07:00 | 200 | 41.5922ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/14 - 19:07:00 | 200 | 2.2299ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/14 - 19:07:07 | 200 | 2.0741ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/14 - 19:07:07 | 200 | 1.4182ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/14 - 19:07:20 | 200 | 3.052ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/14 - 19:07:20 | 200 | 0s | 127.0.0.1 | GET "/" [GIN] 2025/03/14 - 19:07:20 | 200 | 1.0169ms | 127.0.0.1 | GET "/api/tags" time=2025-03-14T19:07:31.281+01:00 level=INFO source=sched.go:186 msg="one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency" time=2025-03-14T19:07:31.300+01:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0 time=2025-03-14T19:07:31.300+01:00 level=INFO source=sched.go:715 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 gpu=0 parallel=4 available=17779961856 required="2.5 GiB" time=2025-03-14T19:07:31.669+01:00 level=INFO source=server.go:105 msg="system memory" total="23.6 GiB" free="13.1 GiB" free_swap="9.4 GiB" time=2025-03-14T19:07:31.671+01:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0 time=2025-03-14T19:07:31.671+01:00 level=INFO source=server.go:138 msg=offload library=rocm layers.requested=-1 layers.model=17 layers.offload=17 layers.split="" memory.available="[16.6 GiB]" memory.gpu_overhead="0 B" memory.required.full="2.5 GiB" memory.required.partial="2.5 GiB" memory.required.kv="256.0 MiB" memory.required.allocations="[2.5 GiB]" memory.weights.total="986.2 MiB" memory.weights.repeating="986.2 MiB" memory.weights.nonrepeating="266.2 MiB" memory.graph.full="544.0 MiB" memory.graph.partial="554.3 MiB" llama_model_loader: loaded meta data with 30 key-value pairs and 147 tensors from C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 (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 = llama llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Llama 3.2 1B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Llama-3.2 llama_model_loader: - kv 5: general.size_label str = 1B llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam... llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ... llama_model_loader: - kv 8: llama.block_count u32 = 16 llama_model_loader: - kv 9: llama.context_length u32 = 131072 llama_model_loader: - kv 10: llama.embedding_length u32 = 2048 llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192 llama_model_loader: - kv 12: llama.attention.head_count u32 = 32 llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000 llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 16: llama.attention.key_length u32 = 64 llama_model_loader: - kv 17: llama.attention.value_length u32 = 64 llama_model_loader: - kv 18: general.file_type u32 = 7 llama_model_loader: - kv 19: llama.vocab_size u32 = 128256 llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 64 llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000 llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009 llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ... llama_model_loader: - kv 29: general.quantization_version u32 = 2 llama_model_loader: - type f32: 34 tensors llama_model_loader: - type q8_0: 113 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q8_0 print_info: file size = 1.22 GiB (8.50 BPW) load: special tokens cache size = 256 load: token to piece cache size = 0.7999 MB print_info: arch = llama print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 1.24 B print_info: general.name = Llama 3.2 1B Instruct print_info: vocab type = BPE print_info: n_vocab = 128256 print_info: n_merges = 280147 print_info: BOS token = 128000 '<|begin_of_text|>' print_info: EOS token = 128009 '<|eot_id|>' print_info: EOT token = 128009 '<|eot_id|>' print_info: EOM token = 128008 '<|eom_id|>' print_info: LF token = 198 'Ċ' print_info: EOG token = 128008 '<|eom_id|>' print_info: EOG token = 128009 '<|eot_id|>' print_info: max token length = 256 llama_model_load: vocab only - skipping tensors time=2025-03-14T19:07:31.833+01:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\donda\\Downloads\\ollama-windows-amd64\\ollama.exe runner --model C:\\Users\\donda\\.ollama\\models\\blobs\\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 --ctx-size 8192 --batch-size 512 --n-gpu-layers 17 --threads 16 --parallel 4 --port 55568" time=2025-03-14T19:07:31.837+01:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-14T19:07:31.838+01:00 level=INFO source=server.go:585 msg="waiting for llama runner to start responding" time=2025-03-14T19:07:31.839+01:00 level=INFO source=server.go:619 msg="waiting for server to become available" status="llm server error" time=2025-03-14T19:07:31.866+01:00 level=INFO source=runner.go:931 msg="starting go runner" 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(TM) 8060S Graphics, gfx1151 (0x1151), VMM: no, Wave Size: 32 load_backend: loaded ROCm backend from C:\Users\donda\Downloads\ollama-windows-amd64\lib\ollama\rocm\ggml-hip.dll load_backend: loaded CPU backend from C:\Users\donda\Downloads\ollama-windows-amd64\lib\ollama\ggml-cpu-icelake.dll time=2025-03-14T19:08:06.787+01:00 level=INFO source=ggml.go:109 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.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) time=2025-03-14T19:08:06.788+01:00 level=INFO source=runner.go:991 msg="Server listening on 127.0.0.1:55568" time=2025-03-14T19:08:06.972+01:00 level=INFO source=server.go:619 msg="waiting for server to become available" status="llm server loading model" llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon(TM) 8060S Graphics) - 17112 MiB free llama_model_loader: loaded meta data with 30 key-value pairs and 147 tensors from C:\Users\donda\.ollama\models\blobs\sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 (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 = llama llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Llama 3.2 1B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Llama-3.2 llama_model_loader: - kv 5: general.size_label str = 1B llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam... llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ... llama_model_loader: - kv 8: llama.block_count u32 = 16 llama_model_loader: - kv 9: llama.context_length u32 = 131072 llama_model_loader: - kv 10: llama.embedding_length u32 = 2048 llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192 llama_model_loader: - kv 12: llama.attention.head_count u32 = 32 llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000 llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 16: llama.attention.key_length u32 = 64 llama_model_loader: - kv 17: llama.attention.value_length u32 = 64 llama_model_loader: - kv 18: general.file_type u32 = 7 llama_model_loader: - kv 19: llama.vocab_size u32 = 128256 llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 64 llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000 llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009 llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ... llama_model_loader: - kv 29: general.quantization_version u32 = 2 llama_model_loader: - type f32: 34 tensors llama_model_loader: - type q8_0: 113 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q8_0 print_info: file size = 1.22 GiB (8.50 BPW) load: special tokens cache size = 256 load: token to piece cache size = 0.7999 MB print_info: arch = llama print_info: vocab_only = 0 print_info: n_ctx_train = 131072 print_info: n_embd = 2048 print_info: n_layer = 16 print_info: n_head = 32 print_info: n_head_kv = 8 print_info: n_rot = 64 print_info: n_swa = 0 print_info: n_embd_head_k = 64 print_info: n_embd_head_v = 64 print_info: n_gqa = 4 print_info: n_embd_k_gqa = 512 print_info: n_embd_v_gqa = 512 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-05 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 8192 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 0 print_info: rope scaling = linear print_info: freq_base_train = 500000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 131072 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 1B print_info: model params = 1.24 B print_info: general.name = Llama 3.2 1B Instruct print_info: vocab type = BPE print_info: n_vocab = 128256 print_info: n_merges = 280147 print_info: BOS token = 128000 '<|begin_of_text|>' print_info: EOS token = 128009 '<|eot_id|>' print_info: EOT token = 128009 '<|eot_id|>' print_info: EOM token = 128008 '<|eom_id|>' print_info: LF token = 198 'Ċ' print_info: EOG token = 128008 '<|eom_id|>' print_info: EOG token = 128009 '<|eot_id|>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = true) load_tensors: offloading 16 repeating layers to GPU load_tensors: offloading output layer to GPU load_tensors: offloaded 17/17 layers to GPU load_tensors: ROCm0 model buffer size = 1252.41 MiB load_tensors: CPU_Mapped model buffer size = 266.16 MiB llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 500000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (131072) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 16, can_shift = 1 llama_kv_cache_init: ROCm0 KV buffer size = 256.00 MiB llama_init_from_model: KV self size = 256.00 MiB, K (f16): 128.00 MiB, V (f16): 128.00 MiB llama_init_from_model: ROCm_Host output buffer size = 1.99 MiB llama_init_from_model: ROCm0 compute buffer size = 544.00 MiB llama_init_from_model: ROCm_Host compute buffer size = 20.01 MiB llama_init_from_model: graph nodes = 518 llama_init_from_model: graph splits = 2 time=2025-03-14T19:08:08.725+01:00 level=INFO source=server.go:624 msg="llama runner started in 36.89 seconds" ggml_cuda_compute_forward: RMS_NORM 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:2315 err C:/a/ollama/ollama/ml/backend/ggml/ggml/src/ggml-cuda/ggml-cuda.cu:73: ROCm error [GIN] 2025/03/14 - 19:08:08 | 200 | 37.8614692s | 127.0.0.1 | POST "/api/chat" time=2025-03-14T19:08:08.931+01:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" ``` ### OS _No response_ ### GPU _No response_ ### CPU _No response_ ### Ollama version _No response_
GiteaMirror added the bug label 2026-04-22 13:07:05 -05:00
GiteaMirror commented 2026-04-22 13:07:08 -05:00
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@zztop007 commented on GitHub (Mar 18, 2025):

I can confirm it seems to work. Thank you.

<!-- gh-comment-id:2734258963 --> @zztop007 commented on GitHub (Mar 18, 2025): I can confirm it seems to work. Thank you.
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Reference: github-starred/ollama#32149
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