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Code Issues 14.5k Packages Projects Releases 120 Wiki Activity

[GH-ISSUE #10980] Ollama Ignores System Prompts When Used with Qwen-Agent RAG Example #7237

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opened 2026-04-12 19:15:45 -05:00 by GiteaMirror · 4 comments
GiteaMirror commented 2026-04-12 19:15:45 -05:00
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Originally created by @Harry-Up on GitHub (Jun 5, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/10980

What is the issue?

Environment

  • ​​OS​​: Windows 11
  • ​​Ollama Version​​: 0.7.0
  • ​​Python​​: 3.11.11
  • ​​Qwen-Agent​​: 0.0.24

​​Tested Models​​:

  • qwen3:30b (local via Ollama)
  • qwen3:14b (local via Ollama)
  • qwen3:14b-q8_0 (local via Ollama)
  • qwq (local via Ollama)

Problem Description
When running the examples/assistant_rag.py from Qwen-Agent with ​​Ollama-served Qwen models​​, the models consistently ​​fail to process RAG tasks​​ (file content is ignored). This occurs ​​only when system prompts are used​​ in their standard position.

Key observations:

​​- Workaround​​: Moving the system prompt to the user prompt position resolves the issue.
​​- Comparison Tests​​:
✅ ​​Aliyun Bailian​​ models (qwen-latest-plus, qwen3:30b, qwen3:8b) handle RAG correctly with system prompts.
✅ ​​vLLM Docker​​ (using unsloth/Qwen3-14B-unsloth-bnb-4bit) also processes RAG successfully.

  • ​​Suspected Root Cause​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models.

Relevant log output

OS

Windows

GPU

Nvidia

CPU

AMD

Ollama version

0.7.0

Originally created by @Harry-Up on GitHub (Jun 5, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/10980 ### What is the issue? **Environment** - ​​OS​​: Windows 11 - ​​Ollama Version​​: 0.7.0 - ​​Python​​: 3.11.11 - ​​Qwen-Agent​​: 0.0.24 **​​Tested Models**​​: - qwen3:30b (local via Ollama) - qwen3:14b (local via Ollama) - qwen3:14b-q8_0 (local via Ollama) - qwq (local via Ollama) **Problem Description** When running the examples/assistant_rag.py from [Qwen-Agent](https://github.com/QwenLM/qwen-agent) with ​​Ollama-served Qwen models​​, the models consistently ​​fail to process RAG tasks​​ (file content is ignored). This occurs ​​only when system prompts are used​​ in their standard position. **Key observations**: ​​- **Workaround​​**: Moving the system prompt to the user prompt position resolves the issue. ​​- **Comparison Tests​​**: ✅ ​​Aliyun Bailian​​ models (qwen-latest-plus, qwen3:30b, qwen3:8b) handle RAG correctly with system prompts. ✅ ​​vLLM Docker​​ (using unsloth/Qwen3-14B-unsloth-bnb-4bit) also processes RAG successfully. - ​​**Suspected Root Cause**​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models. ### Relevant log output ```shell ``` ### OS Windows ### GPU Nvidia ### CPU AMD ### Ollama version 0.7.0
GiteaMirror added the bug label 2026-04-12 19:15:45 -05:00
GiteaMirror commented 2026-04-12 19:15:47 -05:00
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@rick-github commented on GitHub (Jun 5, 2025):

​​Suspected Root Cause​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models.

More likely is that the context is too small. Server logs with OLLAMA_DEBUG=1 will aid in debugging.

<!-- gh-comment-id:2944086771 --> @rick-github commented on GitHub (Jun 5, 2025): > ​​Suspected Root Cause​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models. More likely is that the context is too small. [Server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) with `OLLAMA_DEBUG=1` will aid in debugging.
GiteaMirror commented 2026-04-12 19:15:48 -05:00
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@Harry-Up commented on GitHub (Jun 6, 2025):

​​Suspected Root Cause​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models.

More likely is that the context is too small. Server logs with OLLAMA_DEBUG=1 will aid in debugging.

Yeah, I update Ollama and try it again with OLLAMA_DEBUG=1. The problem keeps as well. Here is the server log.

time=2025-06-06T21:47:24.165+08:00 level=INFO source=routes.go:1234 msg="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:4096 OLLAMA_DEBUG:DEBUG OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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\weihb\.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=2025-06-06T21:47:24.169+08:00 level=INFO source=images.go:479 msg="total blobs: 13"
time=2025-06-06T21:47:24.170+08:00 level=INFO source=images.go:486 msg="total unused blobs removed: 0"
time=2025-06-06T21:47:24.170+08:00 level=INFO source=routes.go:1287 msg="Listening on [::]:11434 (version 0.9.0)"
time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=sched.go:108 msg="starting llm scheduler"
time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=8 efficiency=0 threads=16
time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:98 msg="searching for GPU discovery libraries for NVIDIA"
time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:501 msg="Searching for GPU library" name=nvml.dll
time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:525 msg="gpu library search" globs="[C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\nvml.dll C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin\nvml.dll C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\libnvvp\nvml.dll C:\WINDOWS\system32\nvml.dll C:\WINDOWS\nvml.dll C:\WINDOWS\System32\Wbem\nvml.dll C:\WINDOWS\System32\WindowsPowerShell\v1.0\nvml.dll C:\WINDOWS\System32\OpenSSH\nvml.dll C:\Program Files (x86)\Windows Kits\10\Windows Performance Toolkit\nvml.dll C:\Program Files\NVIDIA Corporation\NVIDIA App\NvDLISR\nvml.dll C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common\nvml.dll C:\Program Files\Git\cmd\nvml.dll C:\Program Files\Docker\Docker\resources\bin\nvml.dll C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.43.34808\bin\Hostx64\x64\nvml.dll C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64\nvml.dll C:\MinGW\bin\nvml.dll C:\Program Files\NVIDIA Corporation\Nsight Compute 2022.3.0\nvml.dll C:\Program Files\dotnet\nvml.dll C:\Users\weihb\AppData\Local\Microsoft\WindowsApps\nvml.dll C:\Users\weihb\AppData\Local\Programs\Microsoft VS Code\bin\nvml.dll C:\Users\weihb\AppData\Local\Programs\Ollama\nvml.dll c:\Windows\System32\nvml.dll]"
time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:529 msg="skipping PhysX cuda library path" path="C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common\nvml.dll"
time=2025-06-06T21:47:24.171+08:00 level=DEBUG source=gpu.go:558 msg="discovered GPU libraries" paths="[C:\WINDOWS\system32\nvml.dll c:\Windows\System32\nvml.dll]"
time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:111 msg="nvidia-ml loaded" library=C:\WINDOWS\system32\nvml.dll
time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:501 msg="Searching for GPU library" name=nvcuda.dll
time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:525 msg="gpu library search" globs="[C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\nvcuda.dll C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin\nvcuda.dll C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\libnvvp\nvcuda.dll C:\WINDOWS\system32\nvcuda.dll C:\WINDOWS\nvcuda.dll C:\WINDOWS\System32\Wbem\nvcuda.dll C:\WINDOWS\System32\WindowsPowerShell\v1.0\nvcuda.dll C:\WINDOWS\System32\OpenSSH\nvcuda.dll C:\Program Files (x86)\Windows Kits\10\Windows Performance Toolkit\nvcuda.dll C:\Program Files\NVIDIA Corporation\NVIDIA App\NvDLISR\nvcuda.dll C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common\nvcuda.dll C:\Program Files\Git\cmd\nvcuda.dll C:\Program Files\Docker\Docker\resources\bin\nvcuda.dll C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.43.34808\bin\Hostx64\x64\nvcuda.dll C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64\nvcuda.dll C:\MinGW\bin\nvcuda.dll C:\Program Files\NVIDIA Corporation\Nsight Compute 2022.3.0\nvcuda.dll C:\Program Files\dotnet\nvcuda.dll C:\Users\weihb\AppData\Local\Microsoft\WindowsApps\nvcuda.dll C:\Users\weihb\AppData\Local\Programs\Microsoft VS Code\bin\nvcuda.dll C:\Users\weihb\AppData\Local\Programs\Ollama\nvcuda.dll c:\windows\system\nvcuda.dll]"
time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:529 msg="skipping PhysX cuda library path" path="C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common\nvcuda.dll"
time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:558 msg="discovered GPU libraries" paths=[C:\WINDOWS\system32\nvcuda.dll]
initializing C:\WINDOWS\system32\nvcuda.dll
dlsym: cuInit - 00007FFE357E5F80
dlsym: cuDriverGetVersion - 00007FFE357E6020
dlsym: cuDeviceGetCount - 00007FFE357E6816
dlsym: cuDeviceGet - 00007FFE357E6810
dlsym: cuDeviceGetAttribute - 00007FFE357E6170
dlsym: cuDeviceGetUuid - 00007FFE357E6822
dlsym: cuDeviceGetName - 00007FFE357E681C
dlsym: cuCtxCreate_v3 - 00007FFE357E6894
dlsym: cuMemGetInfo_v2 - 00007FFE357E6996
dlsym: cuCtxDestroy - 00007FFE357E68A6
calling cuInit
calling cuDriverGetVersion
raw version 0x2f30
CUDA driver version: 12.8
calling cuDeviceGetCount
device count 1
time=2025-06-06T21:47:24.188+08:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=C:\WINDOWS\system32\nvcuda.dll
[GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] CUDA totalMem 32606mb
[GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] CUDA freeMem 30843mb
[GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] Compute Capability 12.0
time=2025-06-06T21:47:24.283+08:00 level=DEBUG source=amd_hip_windows.go:88 msg=hipDriverGetVersion version=60342560
time=2025-06-06T21:47:24.283+08:00 level=INFO source=amd_hip_windows.go:103 msg="AMD ROCm reports no devices found"
time=2025-06-06T21:47:24.283+08:00 level=INFO source=amd_windows.go:49 msg="no compatible amdgpu devices detected"
releasing cuda driver library
releasing nvml library
time=2025-06-06T21:47:24.283+08:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f library=cuda variant=v12 compute=12.0 driver=12.8 name="NVIDIA GeForce RTX 5090 D" total="31.8 GiB" available="30.1 GiB"
[GIN] 2025/06/06 - 21:47:31 | 200 | 582.8µs | 127.0.0.1 | GET "/api/version"
[GIN] 2025/06/06 - 21:47:35 | 200 | 0s | 127.0.0.1 | HEAD "/"
[GIN] 2025/06/06 - 21:47:35 | 200 | 25.7005ms | 127.0.0.1 | GET "/api/tags"
time=2025-06-06T21:48:23.357+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
time=2025-06-06T21:48:23.359+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.5 GiB" before.free_swap="24.0 GiB" now.total="31.6 GiB" now.free="15.0 GiB" now.free_swap="22.9 GiB"
time=2025-06-06T21:48:23.375+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="30.1 GiB" now.total="31.8 GiB" now.free="29.7 GiB" now.used="2.2 GiB"
releasing nvml library
time=2025-06-06T21:48:23.376+08:00 level=DEBUG source=sched.go:185 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1
time=2025-06-06T21:48:23.383+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
time=2025-06-06T21:48:23.391+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
time=2025-06-06T21:48:23.392+08:00 level=DEBUG source=sched.go:228 msg="loading first model" model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac
time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[29.7 GiB]"
time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3moe.vision.block_count default=0
time=2025-06-06T21:48:23.393+08:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f parallel=2 available=31845679104 required="19.8 GiB"
time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.0 GiB" before.free_swap="22.9 GiB" now.total="31.6 GiB" now.free="15.0 GiB" now.free_swap="22.9 GiB"
time=2025-06-06T21:48:23.405+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="29.7 GiB" now.total="31.8 GiB" now.free="29.7 GiB" now.used="2.2 GiB"
releasing nvml library
time=2025-06-06T21:48:23.406+08:00 level=INFO source=server.go:135 msg="system memory" total="31.6 GiB" free="15.0 GiB" free_swap="22.9 GiB"
time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[29.7 GiB]"
time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3moe.vision.block_count default=0
time=2025-06-06T21:48:23.406+08:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[29.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="19.8 GiB" memory.required.partial="19.8 GiB" memory.required.kv="768.0 MiB" memory.required.allocations="[19.8 GiB]" memory.weights.total="17.2 GiB" memory.weights.repeating="16.9 GiB" memory.weights.nonrepeating="243.4 MiB" memory.graph.full="1.0 GiB" memory.graph.partial="1.0 GiB"
time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=server.go:284 msg="compatible gpu libraries" compatible="[cuda_v12 cuda_v11]"
llama_model_loader: loaded meta data with 31 key-value pairs and 579 tensors from C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac (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 = qwen3moe
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3 30B A3B
llama_model_loader: - kv 3: general.basename str = Qwen3
llama_model_loader: - kv 4: general.size_label str = 30B-A3B
llama_model_loader: - kv 5: general.license str = apache-2.0
llama_model_loader: - kv 6: qwen3moe.block_count u32 = 48
llama_model_loader: - kv 7: qwen3moe.context_length u32 = 40960
llama_model_loader: - kv 8: qwen3moe.embedding_length u32 = 2048
llama_model_loader: - kv 9: qwen3moe.feed_forward_length u32 = 6144
llama_model_loader: - kv 10: qwen3moe.attention.head_count u32 = 32
llama_model_loader: - kv 11: qwen3moe.attention.head_count_kv u32 = 4
llama_model_loader: - kv 12: qwen3moe.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 13: qwen3moe.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 14: qwen3moe.expert_used_count u32 = 8
llama_model_loader: - kv 15: qwen3moe.attention.key_length u32 = 128
llama_model_loader: - kv 16: qwen3moe.attention.value_length u32 = 128
llama_model_loader: - kv 17: qwen3moe.expert_count u32 = 128
llama_model_loader: - kv 18: qwen3moe.expert_feed_forward_length u32 = 768
llama_model_loader: - kv 19: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 20: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 21: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 23: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 25: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - kv 30: general.file_type u32 = 15
llama_model_loader: - type f32: 241 tensors
llama_model_loader: - type f16: 48 tensors
llama_model_loader: - type q4_K: 265 tensors
llama_model_loader: - type q6_K: 25 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 17.34 GiB (4.88 BPW)
init_tokenizer: initializing tokenizer for type 2
load: control token: 151659 '<|fim_prefix|>' is not marked as EOG
load: control token: 151656 '<|video_pad|>' is not marked as EOG
load: control token: 151655 '<|image_pad|>' is not marked as EOG
load: control token: 151653 '<|vision_end|>' is not marked as EOG
load: control token: 151652 '<|vision_start|>' is not marked as EOG
load: control token: 151651 '<|quad_end|>' is not marked as EOG
load: control token: 151649 '<|box_end|>' is not marked as EOG
load: control token: 151648 '<|box_start|>' is not marked as EOG
load: control token: 151646 '<|object_ref_start|>' is not marked as EOG
load: control token: 151644 '<|im_start|>' is not marked as EOG
load: control token: 151661 '<|fim_suffix|>' is not marked as EOG
load: control token: 151647 '<|object_ref_end|>' is not marked as EOG
load: control token: 151660 '<|fim_middle|>' is not marked as EOG
load: control token: 151654 '<|vision_pad|>' is not marked as EOG
load: control token: 151650 '<|quad_start|>' is not marked as EOG
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3moe
print_info: vocab_only = 1
print_info: model type = ?B
print_info: model params = 30.53 B
print_info: general.name = Qwen3 30B A3B
print_info: n_ff_exp = 0
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:360 msg="adding gpu library" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12
time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:367 msg="adding gpu dependency paths" paths=[C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12]
time=2025-06-06T21:48:23.529+08:00 level=INFO source=server.go:431 msg="starting llama server" cmd="C:\Users\weihb\AppData\Local\Programs\Ollama\ollama.exe runner --model C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 8 --no-mmap --parallel 2 --port 53373"
time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:432 msg=subprocess CUDA_PATH="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8" OLLAMA_API_KEY=!@#$1234qaZ OLLAMA_DEBUG=1 OLLAMA_HOST=0.0.0.0:11434 OLLAMA_MAX_LOADED_MODELS=3 PATH="C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12;C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12;C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama;C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin;C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\libnvvp;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\System32\OpenSSH\;C:\Program Files (x86)\Windows Kits\10\Windows Performance Toolkit\;C:\Program Files\NVIDIA Corporation\NVIDIA App\NvDLISR;C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common;C:\Program Files\Git\cmd;C:\Program Files\Docker\Docker\resources\bin;C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.43.34808\bin\Hostx64\x64;C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64;C:\MinGW\bin;C:\Program Files\NVIDIA Corporation\Nsight Compute 2022.3.0\;C:\Program Files\dotnet\;C:\Users\weihb\AppData\Local\Microsoft\WindowsApps;C:\Users\weihb\AppData\Local\Programs\Microsoft VS Code\bin;C:\Users\weihb\AppData\Local\Programs\Ollama;C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama" OLLAMA_LIBRARY_PATH=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama;C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12 CUDA_VISIBLE_DEVICES=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f
time=2025-06-06T21:48:23.532+08:00 level=INFO source=sched.go:483 msg="loaded runners" count=1
time=2025-06-06T21:48:23.532+08:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding"
time=2025-06-06T21:48:23.533+08:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error"
time=2025-06-06T21:48:23.556+08:00 level=INFO source=runner.go:815 msg="starting go runner"
time=2025-06-06T21:48:23.559+08:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama
load_backend: loaded CPU backend from C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll
time=2025-06-06T21:48:23.661+08:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 5090 D, compute capability 12.0, VMM: yes
load_backend: loaded CUDA backend from C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll
time=2025-06-06T21:48:39.340+08:00 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 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
time=2025-06-06T21:48:39.341+08:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:53373"
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 5090 D) - 30843 MiB free
llama_model_loader: loaded meta data with 31 key-value pairs and 579 tensors from C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac (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 = qwen3moe
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3 30B A3B
llama_model_loader: - kv 3: general.basename str = Qwen3
llama_model_loader: - kv 4: general.size_label str = 30B-A3B
llama_model_loader: - kv 5: general.license str = apache-2.0
llama_model_loader: - kv 6: qwen3moe.block_count u32 = 48
llama_model_loader: - kv 7: qwen3moe.context_length u32 = 40960
llama_model_loader: - kv 8: qwen3moe.embedding_length u32 = 2048
llama_model_loader: - kv 9: qwen3moe.feed_forward_length u32 = 6144
llama_model_loader: - kv 10: qwen3moe.attention.head_count u32 = 32
llama_model_loader: - kv 11: qwen3moe.attention.head_count_kv u32 = 4
llama_model_loader: - kv 12: qwen3moe.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 13: qwen3moe.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 14: qwen3moe.expert_used_count u32 = 8
llama_model_loader: - kv 15: qwen3moe.attention.key_length u32 = 128
llama_model_loader: - kv 16: qwen3moe.attention.value_length u32 = 128
llama_model_loader: - kv 17: qwen3moe.expert_count u32 = 128
llama_model_loader: - kv 18: qwen3moe.expert_feed_forward_length u32 = 768
llama_model_loader: - kv 19: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 20: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 21: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 23: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 25: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - kv 30: general.file_type u32 = 15
llama_model_loader: - type f32: 241 tensors
llama_model_loader: - type f16: 48 tensors
llama_model_loader: - type q4_K: 265 tensors
llama_model_loader: - type q6_K: 25 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 17.34 GiB (4.88 BPW)
init_tokenizer: initializing tokenizer for type 2
load: control token: 151659 '<|fim_prefix|>' is not marked as EOG
load: control token: 151656 '<|video_pad|>' is not marked as EOG
load: control token: 151655 '<|image_pad|>' is not marked as EOG
load: control token: 151653 '<|vision_end|>' is not marked as EOG
load: control token: 151652 '<|vision_start|>' is not marked as EOG
load: control token: 151651 '<|quad_end|>' is not marked as EOG
load: control token: 151649 '<|box_end|>' is not marked as EOG
load: control token: 151648 '<|box_start|>' is not marked as EOG
load: control token: 151646 '<|object_ref_start|>' is not marked as EOG
load: control token: 151644 '<|im_start|>' is not marked as EOG
load: control token: 151661 '<|fim_suffix|>' is not marked as EOG
load: control token: 151647 '<|object_ref_end|>' is not marked as EOG
load: control token: 151660 '<|fim_middle|>' is not marked as EOG
load: control token: 151654 '<|vision_pad|>' is not marked as EOG
load: control token: 151650 '<|quad_start|>' is not marked as EOG
load: special tokens cache size = 26
time=2025-06-06T21:48:39.553+08:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model"
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3moe
print_info: vocab_only = 0
print_info: n_ctx_train = 40960
print_info: n_embd = 2048
print_info: n_layer = 48
print_info: n_head = 32
print_info: n_head_kv = 4
print_info: n_rot = 128
print_info: n_swa = 0
print_info: n_swa_pattern = 1
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 8
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-06
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: f_attn_scale = 0.0e+00
print_info: n_ff = 6144
print_info: n_expert = 128
print_info: n_expert_used = 8
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 40960
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 = 30B.A3B
print_info: model params = 30.53 B
print_info: general.name = Qwen3 30B A3B
print_info: n_ff_exp = 768
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors: layer 0 assigned to device CUDA0, is_swa = 0
load_tensors: layer 1 assigned to device CUDA0, is_swa = 0
load_tensors: layer 2 assigned to device CUDA0, is_swa = 0
load_tensors: layer 3 assigned to device CUDA0, is_swa = 0
load_tensors: layer 4 assigned to device CUDA0, is_swa = 0
load_tensors: layer 5 assigned to device CUDA0, is_swa = 0
load_tensors: layer 6 assigned to device CUDA0, is_swa = 0
load_tensors: layer 7 assigned to device CUDA0, is_swa = 0
load_tensors: layer 8 assigned to device CUDA0, is_swa = 0
load_tensors: layer 9 assigned to device CUDA0, is_swa = 0
load_tensors: layer 10 assigned to device CUDA0, is_swa = 0
load_tensors: layer 11 assigned to device CUDA0, is_swa = 0
load_tensors: layer 12 assigned to device CUDA0, is_swa = 0
load_tensors: layer 13 assigned to device CUDA0, is_swa = 0
load_tensors: layer 14 assigned to device CUDA0, is_swa = 0
load_tensors: layer 15 assigned to device CUDA0, is_swa = 0
load_tensors: layer 16 assigned to device CUDA0, is_swa = 0
load_tensors: layer 17 assigned to device CUDA0, is_swa = 0
load_tensors: layer 18 assigned to device CUDA0, is_swa = 0
load_tensors: layer 19 assigned to device CUDA0, is_swa = 0
load_tensors: layer 20 assigned to device CUDA0, is_swa = 0
load_tensors: layer 21 assigned to device CUDA0, is_swa = 0
load_tensors: layer 22 assigned to device CUDA0, is_swa = 0
load_tensors: layer 23 assigned to device CUDA0, is_swa = 0
load_tensors: layer 24 assigned to device CUDA0, is_swa = 0
load_tensors: layer 25 assigned to device CUDA0, is_swa = 0
load_tensors: layer 26 assigned to device CUDA0, is_swa = 0
load_tensors: layer 27 assigned to device CUDA0, is_swa = 0
load_tensors: layer 28 assigned to device CUDA0, is_swa = 0
load_tensors: layer 29 assigned to device CUDA0, is_swa = 0
load_tensors: layer 30 assigned to device CUDA0, is_swa = 0
load_tensors: layer 31 assigned to device CUDA0, is_swa = 0
load_tensors: layer 32 assigned to device CUDA0, is_swa = 0
load_tensors: layer 33 assigned to device CUDA0, is_swa = 0
load_tensors: layer 34 assigned to device CUDA0, is_swa = 0
load_tensors: layer 35 assigned to device CUDA0, is_swa = 0
load_tensors: layer 36 assigned to device CUDA0, is_swa = 0
load_tensors: layer 37 assigned to device CUDA0, is_swa = 0
load_tensors: layer 38 assigned to device CUDA0, is_swa = 0
load_tensors: layer 39 assigned to device CUDA0, is_swa = 0
load_tensors: layer 40 assigned to device CUDA0, is_swa = 0
load_tensors: layer 41 assigned to device CUDA0, is_swa = 0
load_tensors: layer 42 assigned to device CUDA0, is_swa = 0
load_tensors: layer 43 assigned to device CUDA0, is_swa = 0
load_tensors: layer 44 assigned to device CUDA0, is_swa = 0
load_tensors: layer 45 assigned to device CUDA0, is_swa = 0
load_tensors: layer 46 assigned to device CUDA0, is_swa = 0
load_tensors: layer 47 assigned to device CUDA0, is_swa = 0
load_tensors: layer 48 assigned to device CUDA0, is_swa = 0
load_tensors: tensor 'token_embd.weight' (q4_K) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead
load_tensors: offloading 48 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 49/49 layers to GPU
load_tensors: CUDA0 model buffer size = 17587.24 MiB
load_tensors: CPU model buffer size = 166.92 MiB
load_all_data: using async uploads for device CUDA0, buffer type CUDA0, backend CUDA0
time=2025-06-06T21:48:39.803+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.00"
time=2025-06-06T21:48:40.053+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.03"
time=2025-06-06T21:48:40.304+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.06"
time=2025-06-06T21:48:40.554+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.09"
time=2025-06-06T21:48:40.804+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.11"
time=2025-06-06T21:48:41.054+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.14"
time=2025-06-06T21:48:41.304+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.18"
time=2025-06-06T21:48:41.555+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.20"
time=2025-06-06T21:48:41.805+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.22"
time=2025-06-06T21:48:42.056+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.25"
time=2025-06-06T21:48:42.306+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.28"
time=2025-06-06T21:48:42.556+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.31"
time=2025-06-06T21:48:42.806+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.33"
time=2025-06-06T21:48:43.056+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.35"
time=2025-06-06T21:48:43.307+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.38"
time=2025-06-06T21:48:43.557+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.40"
time=2025-06-06T21:48:43.807+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.43"
time=2025-06-06T21:48:44.057+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.46"
time=2025-06-06T21:48:44.308+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.49"
time=2025-06-06T21:48:44.558+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.52"
time=2025-06-06T21:48:44.809+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.55"
time=2025-06-06T21:48:45.059+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.58"
time=2025-06-06T21:48:45.309+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.61"
time=2025-06-06T21:48:45.559+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.63"
time=2025-06-06T21:48:45.810+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.67"
time=2025-06-06T21:48:46.060+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.69"
time=2025-06-06T21:48:46.311+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.72"
time=2025-06-06T21:48:46.561+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.75"
time=2025-06-06T21:48:46.811+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.78"
time=2025-06-06T21:48:47.062+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.80"
time=2025-06-06T21:48:47.312+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.82"
time=2025-06-06T21:48:47.563+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.85"
time=2025-06-06T21:48:47.813+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.88"
time=2025-06-06T21:48:48.063+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.91"
time=2025-06-06T21:48:48.314+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.93"
time=2025-06-06T21:48:48.564+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.97"
time=2025-06-06T21:48:48.814+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.98"
load_all_data: no device found for buffer type CPU for async uploads
llama_context: constructing llama_context
llama_context: n_seq_max = 2
llama_context: n_ctx = 8192
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch = 1024
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = 0
llama_context: freq_base = 1000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
set_abort_callback: call
llama_context: CUDA_Host output buffer size = 1.17 MiB
create_memory: n_ctx = 8192 (padded)
llama_kv_cache_unified: kv_size = 8192, type_k = 'f16', type_v = 'f16', n_layer = 48, can_shift = 1, padding = 32
llama_kv_cache_unified: layer 0: dev = CUDA0
llama_kv_cache_unified: layer 1: dev = CUDA0
llama_kv_cache_unified: layer 2: dev = CUDA0
llama_kv_cache_unified: layer 3: dev = CUDA0
llama_kv_cache_unified: layer 4: dev = CUDA0
llama_kv_cache_unified: layer 5: dev = CUDA0
llama_kv_cache_unified: layer 6: dev = CUDA0
llama_kv_cache_unified: layer 7: dev = CUDA0
llama_kv_cache_unified: layer 8: dev = CUDA0
llama_kv_cache_unified: layer 9: dev = CUDA0
llama_kv_cache_unified: layer 10: dev = CUDA0
llama_kv_cache_unified: layer 11: dev = CUDA0
llama_kv_cache_unified: layer 12: dev = CUDA0
llama_kv_cache_unified: layer 13: dev = CUDA0
llama_kv_cache_unified: layer 14: dev = CUDA0
llama_kv_cache_unified: layer 15: dev = CUDA0
llama_kv_cache_unified: layer 16: dev = CUDA0
llama_kv_cache_unified: layer 17: dev = CUDA0
llama_kv_cache_unified: layer 18: dev = CUDA0
llama_kv_cache_unified: layer 19: dev = CUDA0
llama_kv_cache_unified: layer 20: dev = CUDA0
llama_kv_cache_unified: layer 21: dev = CUDA0
llama_kv_cache_unified: layer 22: dev = CUDA0
llama_kv_cache_unified: layer 23: dev = CUDA0
llama_kv_cache_unified: layer 24: dev = CUDA0
llama_kv_cache_unified: layer 25: dev = CUDA0
llama_kv_cache_unified: layer 26: dev = CUDA0
llama_kv_cache_unified: layer 27: dev = CUDA0
llama_kv_cache_unified: layer 28: dev = CUDA0
llama_kv_cache_unified: layer 29: dev = CUDA0
llama_kv_cache_unified: layer 30: dev = CUDA0
llama_kv_cache_unified: layer 31: dev = CUDA0
llama_kv_cache_unified: layer 32: dev = CUDA0
llama_kv_cache_unified: layer 33: dev = CUDA0
llama_kv_cache_unified: layer 34: dev = CUDA0
llama_kv_cache_unified: layer 35: dev = CUDA0
llama_kv_cache_unified: layer 36: dev = CUDA0
llama_kv_cache_unified: layer 37: dev = CUDA0
llama_kv_cache_unified: layer 38: dev = CUDA0
llama_kv_cache_unified: layer 39: dev = CUDA0
llama_kv_cache_unified: layer 40: dev = CUDA0
llama_kv_cache_unified: layer 41: dev = CUDA0
llama_kv_cache_unified: layer 42: dev = CUDA0
llama_kv_cache_unified: layer 43: dev = CUDA0
llama_kv_cache_unified: layer 44: dev = CUDA0
llama_kv_cache_unified: layer 45: dev = CUDA0
llama_kv_cache_unified: layer 46: dev = CUDA0
llama_kv_cache_unified: layer 47: dev = CUDA0
llama_kv_cache_unified: CUDA0 KV buffer size = 768.00 MiB
llama_kv_cache_unified: KV self size = 768.00 MiB, K (f16): 384.00 MiB, V (f16): 384.00 MiB
llama_context: enumerating backends
llama_context: backend_ptrs.size() = 2
llama_context: max_nodes = 65536
llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
llama_context: reserving graph for n_tokens = 512, n_seqs = 1
llama_context: reserving graph for n_tokens = 1, n_seqs = 1
llama_context: reserving graph for n_tokens = 512, n_seqs = 1
llama_context: CUDA0 compute buffer size = 552.00 MiB
llama_context: CUDA_Host compute buffer size = 20.01 MiB
llama_context: graph nodes = 3126
llama_context: graph splits = 2
time=2025-06-06T21:48:49.065+08:00 level=INFO source=server.go:630 msg="llama runner started in 25.53 seconds"
time=2025-06-06T21:48:49.065+08:00 level=DEBUG source=sched.go:495 msg="finished setting up" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192
time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2
time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=server.go:729 msg="completion request" images=0 prompt=104 format=""
time=2025-06-06T21:48:49.090+08:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=30 used=0 remaining=30
[GIN] 2025/06/06 - 21:48:51 | 200 | 28.6746475s | 127.0.0.1 | POST "/v1/chat/completions"
time=2025-06-06T21:48:51.995+08:00 level=DEBUG source=sched.go:503 msg="context for request finished"
time=2025-06-06T21:48:51.996+08:00 level=DEBUG source=sched.go:343 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 duration=5m0s
time=2025-06-06T21:48:51.996+08:00 level=DEBUG source=sched.go:361 msg="after processing request finished event" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 refCount=0
time=2025-06-06T21:53:52.004+08:00 level=DEBUG source=sched.go:345 msg="timer expired, expiring to unload" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192
time=2025-06-06T21:53:52.004+08:00 level=DEBUG source=sched.go:364 msg="runner expired event received" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192
time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=sched.go:379 msg="got lock to unload expired event" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192
time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=sched.go:402 msg="starting background wait for VRAM recovery" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192
time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.0 GiB" before.free_swap="22.9 GiB" now.total="31.6 GiB" now.free="16.8 GiB" now.free_swap="3.0 GiB"
time=2025-06-06T21:53:52.021+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="29.7 GiB" now.total="31.8 GiB" now.free="10.6 GiB" now.used="21.3 GiB"
releasing nvml library
time=2025-06-06T21:53:52.039+08:00 level=DEBUG source=server.go:1023 msg="stopping llama server" pid=27056
time=2025-06-06T21:53:52.039+08:00 level=DEBUG source=server.go:1029 msg="waiting for llama server to exit" pid=27056
time=2025-06-06T21:53:52.164+08:00 level=DEBUG source=server.go:1033 msg="llama server stopped" pid=27056
time=2025-06-06T21:53:52.164+08:00 level=DEBUG source=sched.go:407 msg="runner terminated and removed from list, blocking for VRAM recovery" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac
time=2025-06-06T21:53:52.272+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="16.8 GiB" before.free_swap="3.0 GiB" now.total="31.6 GiB" now.free="17.6 GiB" now.free_swap="23.5 GiB"
time=2025-06-06T21:53:52.285+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="10.6 GiB" now.total="31.8 GiB" now.free="29.6 GiB" now.used="2.2 GiB"
releasing nvml library
time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:700 msg="gpu VRAM free memory converged after 0.28 seconds" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac
time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:410 msg="sending an unloaded event" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac
time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:312 msg="ignoring unload event with no pending requests"

<!-- gh-comment-id:2949354865 --> @Harry-Up commented on GitHub (Jun 6, 2025): > > ​​Suspected Root Cause​​: Ollama's template engine ​​may not inject system prompts correctly​​ for Qwen models. > > More likely is that the context is too small. [Server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) with `OLLAMA_DEBUG=1` will aid in debugging. Yeah, I update Ollama and try it again with `OLLAMA_DEBUG=1`. The problem keeps as well. Here is the server log. time=2025-06-06T21:47:24.165+08:00 level=INFO source=routes.go:1234 msg="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:4096 OLLAMA_DEBUG:DEBUG OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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\\weihb\\.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=2025-06-06T21:47:24.169+08:00 level=INFO source=images.go:479 msg="total blobs: 13" time=2025-06-06T21:47:24.170+08:00 level=INFO source=images.go:486 msg="total unused blobs removed: 0" time=2025-06-06T21:47:24.170+08:00 level=INFO source=routes.go:1287 msg="Listening on [::]:11434 (version 0.9.0)" time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=sched.go:108 msg="starting llm scheduler" time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-06-06T21:47:24.170+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=8 efficiency=0 threads=16 time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:98 msg="searching for GPU discovery libraries for NVIDIA" time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:501 msg="Searching for GPU library" name=nvml.dll time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:525 msg="gpu library search" globs="[C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\nvml.dll C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\bin\\nvml.dll C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\libnvvp\\nvml.dll C:\\WINDOWS\\system32\\nvml.dll C:\\WINDOWS\\nvml.dll C:\\WINDOWS\\System32\\Wbem\\nvml.dll C:\\WINDOWS\\System32\\WindowsPowerShell\\v1.0\\nvml.dll C:\\WINDOWS\\System32\\OpenSSH\\nvml.dll C:\\Program Files (x86)\\Windows Kits\\10\\Windows Performance Toolkit\\nvml.dll C:\\Program Files\\NVIDIA Corporation\\NVIDIA App\\NvDLISR\\nvml.dll C:\\Program Files (x86)\\NVIDIA Corporation\\PhysX\\Common\\nvml.dll C:\\Program Files\\Git\\cmd\\nvml.dll C:\\Program Files\\Docker\\Docker\\resources\\bin\\nvml.dll C:\\Program Files\\Microsoft Visual Studio\\2022\\Community\\VC\\Tools\\MSVC\\14.43.34808\\bin\\Hostx64\\x64\\nvml.dll C:\\Program Files (x86)\\Windows Kits\\10\\bin\\10.0.22621.0\\x64\\nvml.dll C:\\MinGW\\bin\\nvml.dll C:\\Program Files\\NVIDIA Corporation\\Nsight Compute 2022.3.0\\nvml.dll C:\\Program Files\\dotnet\\nvml.dll C:\\Users\\weihb\\AppData\\Local\\Microsoft\\WindowsApps\\nvml.dll C:\\Users\\weihb\\AppData\\Local\\Programs\\Microsoft VS Code\\bin\\nvml.dll C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\nvml.dll c:\\Windows\\System32\\nvml.dll]" time=2025-06-06T21:47:24.170+08:00 level=DEBUG source=gpu.go:529 msg="skipping PhysX cuda library path" path="C:\\Program Files (x86)\\NVIDIA Corporation\\PhysX\\Common\\nvml.dll" time=2025-06-06T21:47:24.171+08:00 level=DEBUG source=gpu.go:558 msg="discovered GPU libraries" paths="[C:\\WINDOWS\\system32\\nvml.dll c:\\Windows\\System32\\nvml.dll]" time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:111 msg="nvidia-ml loaded" library=C:\WINDOWS\system32\nvml.dll time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:501 msg="Searching for GPU library" name=nvcuda.dll time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:525 msg="gpu library search" globs="[C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\nvcuda.dll C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\bin\\nvcuda.dll C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\libnvvp\\nvcuda.dll C:\\WINDOWS\\system32\\nvcuda.dll C:\\WINDOWS\\nvcuda.dll C:\\WINDOWS\\System32\\Wbem\\nvcuda.dll C:\\WINDOWS\\System32\\WindowsPowerShell\\v1.0\\nvcuda.dll C:\\WINDOWS\\System32\\OpenSSH\\nvcuda.dll C:\\Program Files (x86)\\Windows Kits\\10\\Windows Performance Toolkit\\nvcuda.dll C:\\Program Files\\NVIDIA Corporation\\NVIDIA App\\NvDLISR\\nvcuda.dll C:\\Program Files (x86)\\NVIDIA Corporation\\PhysX\\Common\\nvcuda.dll C:\\Program Files\\Git\\cmd\\nvcuda.dll C:\\Program Files\\Docker\\Docker\\resources\\bin\\nvcuda.dll C:\\Program Files\\Microsoft Visual Studio\\2022\\Community\\VC\\Tools\\MSVC\\14.43.34808\\bin\\Hostx64\\x64\\nvcuda.dll C:\\Program Files (x86)\\Windows Kits\\10\\bin\\10.0.22621.0\\x64\\nvcuda.dll C:\\MinGW\\bin\\nvcuda.dll C:\\Program Files\\NVIDIA Corporation\\Nsight Compute 2022.3.0\\nvcuda.dll C:\\Program Files\\dotnet\\nvcuda.dll C:\\Users\\weihb\\AppData\\Local\\Microsoft\\WindowsApps\\nvcuda.dll C:\\Users\\weihb\\AppData\\Local\\Programs\\Microsoft VS Code\\bin\\nvcuda.dll C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\nvcuda.dll c:\\windows\\system*\\nvcuda.dll]" time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:529 msg="skipping PhysX cuda library path" path="C:\\Program Files (x86)\\NVIDIA Corporation\\PhysX\\Common\\nvcuda.dll" time=2025-06-06T21:47:24.180+08:00 level=DEBUG source=gpu.go:558 msg="discovered GPU libraries" paths=[C:\WINDOWS\system32\nvcuda.dll] initializing C:\WINDOWS\system32\nvcuda.dll dlsym: cuInit - 00007FFE357E5F80 dlsym: cuDriverGetVersion - 00007FFE357E6020 dlsym: cuDeviceGetCount - 00007FFE357E6816 dlsym: cuDeviceGet - 00007FFE357E6810 dlsym: cuDeviceGetAttribute - 00007FFE357E6170 dlsym: cuDeviceGetUuid - 00007FFE357E6822 dlsym: cuDeviceGetName - 00007FFE357E681C dlsym: cuCtxCreate_v3 - 00007FFE357E6894 dlsym: cuMemGetInfo_v2 - 00007FFE357E6996 dlsym: cuCtxDestroy - 00007FFE357E68A6 calling cuInit calling cuDriverGetVersion raw version 0x2f30 CUDA driver version: 12.8 calling cuDeviceGetCount device count 1 time=2025-06-06T21:47:24.188+08:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=C:\WINDOWS\system32\nvcuda.dll [GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] CUDA totalMem 32606mb [GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] CUDA freeMem 30843mb [GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f] Compute Capability 12.0 time=2025-06-06T21:47:24.283+08:00 level=DEBUG source=amd_hip_windows.go:88 msg=hipDriverGetVersion version=60342560 time=2025-06-06T21:47:24.283+08:00 level=INFO source=amd_hip_windows.go:103 msg="AMD ROCm reports no devices found" time=2025-06-06T21:47:24.283+08:00 level=INFO source=amd_windows.go:49 msg="no compatible amdgpu devices detected" releasing cuda driver library releasing nvml library time=2025-06-06T21:47:24.283+08:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f library=cuda variant=v12 compute=12.0 driver=12.8 name="NVIDIA GeForce RTX 5090 D" total="31.8 GiB" available="30.1 GiB" [GIN] 2025/06/06 - 21:47:31 | 200 | 582.8µs | 127.0.0.1 | GET "/api/version" [GIN] 2025/06/06 - 21:47:35 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/06/06 - 21:47:35 | 200 | 25.7005ms | 127.0.0.1 | GET "/api/tags" time=2025-06-06T21:48:23.357+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 time=2025-06-06T21:48:23.359+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.5 GiB" before.free_swap="24.0 GiB" now.total="31.6 GiB" now.free="15.0 GiB" now.free_swap="22.9 GiB" time=2025-06-06T21:48:23.375+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="30.1 GiB" now.total="31.8 GiB" now.free="29.7 GiB" now.used="2.2 GiB" releasing nvml library time=2025-06-06T21:48:23.376+08:00 level=DEBUG source=sched.go:185 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1 time=2025-06-06T21:48:23.383+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 time=2025-06-06T21:48:23.391+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 time=2025-06-06T21:48:23.392+08:00 level=DEBUG source=sched.go:228 msg="loading first model" model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[29.7 GiB]" time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3moe.vision.block_count default=0 time=2025-06-06T21:48:23.393+08:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f parallel=2 available=31845679104 required="19.8 GiB" time=2025-06-06T21:48:23.393+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.0 GiB" before.free_swap="22.9 GiB" now.total="31.6 GiB" now.free="15.0 GiB" now.free_swap="22.9 GiB" time=2025-06-06T21:48:23.405+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="29.7 GiB" now.total="31.8 GiB" now.free="29.7 GiB" now.used="2.2 GiB" releasing nvml library time=2025-06-06T21:48:23.406+08:00 level=INFO source=server.go:135 msg="system memory" total="31.6 GiB" free="15.0 GiB" free_swap="22.9 GiB" time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[29.7 GiB]" time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3moe.vision.block_count default=0 time=2025-06-06T21:48:23.406+08:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[29.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="19.8 GiB" memory.required.partial="19.8 GiB" memory.required.kv="768.0 MiB" memory.required.allocations="[19.8 GiB]" memory.weights.total="17.2 GiB" memory.weights.repeating="16.9 GiB" memory.weights.nonrepeating="243.4 MiB" memory.graph.full="1.0 GiB" memory.graph.partial="1.0 GiB" time=2025-06-06T21:48:23.406+08:00 level=DEBUG source=server.go:284 msg="compatible gpu libraries" compatible="[cuda_v12 cuda_v11]" llama_model_loader: loaded meta data with 31 key-value pairs and 579 tensors from C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac (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 = qwen3moe llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen3 30B A3B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 30B-A3B llama_model_loader: - kv 5: general.license str = apache-2.0 llama_model_loader: - kv 6: qwen3moe.block_count u32 = 48 llama_model_loader: - kv 7: qwen3moe.context_length u32 = 40960 llama_model_loader: - kv 8: qwen3moe.embedding_length u32 = 2048 llama_model_loader: - kv 9: qwen3moe.feed_forward_length u32 = 6144 llama_model_loader: - kv 10: qwen3moe.attention.head_count u32 = 32 llama_model_loader: - kv 11: qwen3moe.attention.head_count_kv u32 = 4 llama_model_loader: - kv 12: qwen3moe.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 13: qwen3moe.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 14: qwen3moe.expert_used_count u32 = 8 llama_model_loader: - kv 15: qwen3moe.attention.key_length u32 = 128 llama_model_loader: - kv 16: qwen3moe.attention.value_length u32 = 128 llama_model_loader: - kv 17: qwen3moe.expert_count u32 = 128 llama_model_loader: - kv 18: qwen3moe.expert_feed_forward_length u32 = 768 llama_model_loader: - kv 19: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 20: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 21: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 23: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 25: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 29: general.quantization_version u32 = 2 llama_model_loader: - kv 30: general.file_type u32 = 15 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type f16: 48 tensors llama_model_loader: - type q4_K: 265 tensors llama_model_loader: - type q6_K: 25 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 17.34 GiB (4.88 BPW) init_tokenizer: initializing tokenizer for type 2 load: control token: 151659 '<|fim_prefix|>' is not marked as EOG load: control token: 151656 '<|video_pad|>' is not marked as EOG load: control token: 151655 '<|image_pad|>' is not marked as EOG load: control token: 151653 '<|vision_end|>' is not marked as EOG load: control token: 151652 '<|vision_start|>' is not marked as EOG load: control token: 151651 '<|quad_end|>' is not marked as EOG load: control token: 151649 '<|box_end|>' is not marked as EOG load: control token: 151648 '<|box_start|>' is not marked as EOG load: control token: 151646 '<|object_ref_start|>' is not marked as EOG load: control token: 151644 '<|im_start|>' is not marked as EOG load: control token: 151661 '<|fim_suffix|>' is not marked as EOG load: control token: 151647 '<|object_ref_end|>' is not marked as EOG load: control token: 151660 '<|fim_middle|>' is not marked as EOG load: control token: 151654 '<|vision_pad|>' is not marked as EOG load: control token: 151650 '<|quad_start|>' is not marked as EOG load: special tokens cache size = 26 load: token to piece cache size = 0.9311 MB print_info: arch = qwen3moe print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 30.53 B print_info: general.name = Qwen3 30B A3B print_info: n_ff_exp = 0 print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 llama_model_load: vocab only - skipping tensors time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:360 msg="adding gpu library" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12 time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:367 msg="adding gpu dependency paths" paths=[C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12] time=2025-06-06T21:48:23.529+08:00 level=INFO source=server.go:431 msg="starting llama server" cmd="C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\weihb\\.ollama\\models\\blobs\\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 8 --no-mmap --parallel 2 --port 53373" time=2025-06-06T21:48:23.529+08:00 level=DEBUG source=server.go:432 msg=subprocess CUDA_PATH="C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8" OLLAMA_API_KEY=!@#$1234qaZ OLLAMA_DEBUG=1 OLLAMA_HOST=0.0.0.0:11434 OLLAMA_MAX_LOADED_MODELS=3 PATH="C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\cuda_v12;C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\cuda_v12;C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama;C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\bin;C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.8\\libnvvp;C:\\WINDOWS\\system32;C:\\WINDOWS;C:\\WINDOWS\\System32\\Wbem;C:\\WINDOWS\\System32\\WindowsPowerShell\\v1.0\\;C:\\WINDOWS\\System32\\OpenSSH\\;C:\\Program Files (x86)\\Windows Kits\\10\\Windows Performance Toolkit\\;C:\\Program Files\\NVIDIA Corporation\\NVIDIA App\\NvDLISR;C:\\Program Files (x86)\\NVIDIA Corporation\\PhysX\\Common;C:\\Program Files\\Git\\cmd;C:\\Program Files\\Docker\\Docker\\resources\\bin;C:\\Program Files\\Microsoft Visual Studio\\2022\\Community\\VC\\Tools\\MSVC\\14.43.34808\\bin\\Hostx64\\x64;C:\\Program Files (x86)\\Windows Kits\\10\\bin\\10.0.22621.0\\x64;C:\\MinGW\\bin;C:\\Program Files\\NVIDIA Corporation\\Nsight Compute 2022.3.0\\;C:\\Program Files\\dotnet\\;C:\\Users\\weihb\\AppData\\Local\\Microsoft\\WindowsApps;C:\\Users\\weihb\\AppData\\Local\\Programs\\Microsoft VS Code\\bin;C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama;C:\\Users\\weihb\\AppData\\Local\\Programs\\Ollama\\lib\\ollama" OLLAMA_LIBRARY_PATH=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama;C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12 CUDA_VISIBLE_DEVICES=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f time=2025-06-06T21:48:23.532+08:00 level=INFO source=sched.go:483 msg="loaded runners" count=1 time=2025-06-06T21:48:23.532+08:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding" time=2025-06-06T21:48:23.533+08:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error" time=2025-06-06T21:48:23.556+08:00 level=INFO source=runner.go:815 msg="starting go runner" time=2025-06-06T21:48:23.559+08:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama load_backend: loaded CPU backend from C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-icelake.dll time=2025-06-06T21:48:23.661+08:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12 ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 5090 D, compute capability 12.0, VMM: yes load_backend: loaded CUDA backend from C:\Users\weihb\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll time=2025-06-06T21:48:39.340+08:00 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 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang) time=2025-06-06T21:48:39.341+08:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:53373" llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 5090 D) - 30843 MiB free llama_model_loader: loaded meta data with 31 key-value pairs and 579 tensors from C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac (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 = qwen3moe llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen3 30B A3B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 30B-A3B llama_model_loader: - kv 5: general.license str = apache-2.0 llama_model_loader: - kv 6: qwen3moe.block_count u32 = 48 llama_model_loader: - kv 7: qwen3moe.context_length u32 = 40960 llama_model_loader: - kv 8: qwen3moe.embedding_length u32 = 2048 llama_model_loader: - kv 9: qwen3moe.feed_forward_length u32 = 6144 llama_model_loader: - kv 10: qwen3moe.attention.head_count u32 = 32 llama_model_loader: - kv 11: qwen3moe.attention.head_count_kv u32 = 4 llama_model_loader: - kv 12: qwen3moe.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 13: qwen3moe.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 14: qwen3moe.expert_used_count u32 = 8 llama_model_loader: - kv 15: qwen3moe.attention.key_length u32 = 128 llama_model_loader: - kv 16: qwen3moe.attention.value_length u32 = 128 llama_model_loader: - kv 17: qwen3moe.expert_count u32 = 128 llama_model_loader: - kv 18: qwen3moe.expert_feed_forward_length u32 = 768 llama_model_loader: - kv 19: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 20: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 21: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 23: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 25: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 29: general.quantization_version u32 = 2 llama_model_loader: - kv 30: general.file_type u32 = 15 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type f16: 48 tensors llama_model_loader: - type q4_K: 265 tensors llama_model_loader: - type q6_K: 25 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 17.34 GiB (4.88 BPW) init_tokenizer: initializing tokenizer for type 2 load: control token: 151659 '<|fim_prefix|>' is not marked as EOG load: control token: 151656 '<|video_pad|>' is not marked as EOG load: control token: 151655 '<|image_pad|>' is not marked as EOG load: control token: 151653 '<|vision_end|>' is not marked as EOG load: control token: 151652 '<|vision_start|>' is not marked as EOG load: control token: 151651 '<|quad_end|>' is not marked as EOG load: control token: 151649 '<|box_end|>' is not marked as EOG load: control token: 151648 '<|box_start|>' is not marked as EOG load: control token: 151646 '<|object_ref_start|>' is not marked as EOG load: control token: 151644 '<|im_start|>' is not marked as EOG load: control token: 151661 '<|fim_suffix|>' is not marked as EOG load: control token: 151647 '<|object_ref_end|>' is not marked as EOG load: control token: 151660 '<|fim_middle|>' is not marked as EOG load: control token: 151654 '<|vision_pad|>' is not marked as EOG load: control token: 151650 '<|quad_start|>' is not marked as EOG load: special tokens cache size = 26 time=2025-06-06T21:48:39.553+08:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model" load: token to piece cache size = 0.9311 MB print_info: arch = qwen3moe print_info: vocab_only = 0 print_info: n_ctx_train = 40960 print_info: n_embd = 2048 print_info: n_layer = 48 print_info: n_head = 32 print_info: n_head_kv = 4 print_info: n_rot = 128 print_info: n_swa = 0 print_info: n_swa_pattern = 1 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 8 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-06 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: f_attn_scale = 0.0e+00 print_info: n_ff = 6144 print_info: n_expert = 128 print_info: n_expert_used = 8 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 2 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 40960 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 = 30B.A3B print_info: model params = 30.53 B print_info: general.name = Qwen3 30B A3B print_info: n_ff_exp = 768 print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: layer 0 assigned to device CUDA0, is_swa = 0 load_tensors: layer 1 assigned to device CUDA0, is_swa = 0 load_tensors: layer 2 assigned to device CUDA0, is_swa = 0 load_tensors: layer 3 assigned to device CUDA0, is_swa = 0 load_tensors: layer 4 assigned to device CUDA0, is_swa = 0 load_tensors: layer 5 assigned to device CUDA0, is_swa = 0 load_tensors: layer 6 assigned to device CUDA0, is_swa = 0 load_tensors: layer 7 assigned to device CUDA0, is_swa = 0 load_tensors: layer 8 assigned to device CUDA0, is_swa = 0 load_tensors: layer 9 assigned to device CUDA0, is_swa = 0 load_tensors: layer 10 assigned to device CUDA0, is_swa = 0 load_tensors: layer 11 assigned to device CUDA0, is_swa = 0 load_tensors: layer 12 assigned to device CUDA0, is_swa = 0 load_tensors: layer 13 assigned to device CUDA0, is_swa = 0 load_tensors: layer 14 assigned to device CUDA0, is_swa = 0 load_tensors: layer 15 assigned to device CUDA0, is_swa = 0 load_tensors: layer 16 assigned to device CUDA0, is_swa = 0 load_tensors: layer 17 assigned to device CUDA0, is_swa = 0 load_tensors: layer 18 assigned to device CUDA0, is_swa = 0 load_tensors: layer 19 assigned to device CUDA0, is_swa = 0 load_tensors: layer 20 assigned to device CUDA0, is_swa = 0 load_tensors: layer 21 assigned to device CUDA0, is_swa = 0 load_tensors: layer 22 assigned to device CUDA0, is_swa = 0 load_tensors: layer 23 assigned to device CUDA0, is_swa = 0 load_tensors: layer 24 assigned to device CUDA0, is_swa = 0 load_tensors: layer 25 assigned to device CUDA0, is_swa = 0 load_tensors: layer 26 assigned to device CUDA0, is_swa = 0 load_tensors: layer 27 assigned to device CUDA0, is_swa = 0 load_tensors: layer 28 assigned to device CUDA0, is_swa = 0 load_tensors: layer 29 assigned to device CUDA0, is_swa = 0 load_tensors: layer 30 assigned to device CUDA0, is_swa = 0 load_tensors: layer 31 assigned to device CUDA0, is_swa = 0 load_tensors: layer 32 assigned to device CUDA0, is_swa = 0 load_tensors: layer 33 assigned to device CUDA0, is_swa = 0 load_tensors: layer 34 assigned to device CUDA0, is_swa = 0 load_tensors: layer 35 assigned to device CUDA0, is_swa = 0 load_tensors: layer 36 assigned to device CUDA0, is_swa = 0 load_tensors: layer 37 assigned to device CUDA0, is_swa = 0 load_tensors: layer 38 assigned to device CUDA0, is_swa = 0 load_tensors: layer 39 assigned to device CUDA0, is_swa = 0 load_tensors: layer 40 assigned to device CUDA0, is_swa = 0 load_tensors: layer 41 assigned to device CUDA0, is_swa = 0 load_tensors: layer 42 assigned to device CUDA0, is_swa = 0 load_tensors: layer 43 assigned to device CUDA0, is_swa = 0 load_tensors: layer 44 assigned to device CUDA0, is_swa = 0 load_tensors: layer 45 assigned to device CUDA0, is_swa = 0 load_tensors: layer 46 assigned to device CUDA0, is_swa = 0 load_tensors: layer 47 assigned to device CUDA0, is_swa = 0 load_tensors: layer 48 assigned to device CUDA0, is_swa = 0 load_tensors: tensor 'token_embd.weight' (q4_K) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead load_tensors: offloading 48 repeating layers to GPU load_tensors: offloading output layer to GPU load_tensors: offloaded 49/49 layers to GPU load_tensors: CUDA0 model buffer size = 17587.24 MiB load_tensors: CPU model buffer size = 166.92 MiB load_all_data: using async uploads for device CUDA0, buffer type CUDA0, backend CUDA0 time=2025-06-06T21:48:39.803+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.00" time=2025-06-06T21:48:40.053+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.03" time=2025-06-06T21:48:40.304+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.06" time=2025-06-06T21:48:40.554+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.09" time=2025-06-06T21:48:40.804+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.11" time=2025-06-06T21:48:41.054+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.14" time=2025-06-06T21:48:41.304+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.18" time=2025-06-06T21:48:41.555+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.20" time=2025-06-06T21:48:41.805+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.22" time=2025-06-06T21:48:42.056+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.25" time=2025-06-06T21:48:42.306+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.28" time=2025-06-06T21:48:42.556+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.31" time=2025-06-06T21:48:42.806+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.33" time=2025-06-06T21:48:43.056+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.35" time=2025-06-06T21:48:43.307+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.38" time=2025-06-06T21:48:43.557+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.40" time=2025-06-06T21:48:43.807+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.43" time=2025-06-06T21:48:44.057+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.46" time=2025-06-06T21:48:44.308+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.49" time=2025-06-06T21:48:44.558+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.52" time=2025-06-06T21:48:44.809+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.55" time=2025-06-06T21:48:45.059+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.58" time=2025-06-06T21:48:45.309+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.61" time=2025-06-06T21:48:45.559+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.63" time=2025-06-06T21:48:45.810+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.67" time=2025-06-06T21:48:46.060+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.69" time=2025-06-06T21:48:46.311+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.72" time=2025-06-06T21:48:46.561+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.75" time=2025-06-06T21:48:46.811+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.78" time=2025-06-06T21:48:47.062+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.80" time=2025-06-06T21:48:47.312+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.82" time=2025-06-06T21:48:47.563+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.85" time=2025-06-06T21:48:47.813+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.88" time=2025-06-06T21:48:48.063+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.91" time=2025-06-06T21:48:48.314+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.93" time=2025-06-06T21:48:48.564+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.97" time=2025-06-06T21:48:48.814+08:00 level=DEBUG source=server.go:636 msg="model load progress 0.98" load_all_data: no device found for buffer type CPU for async uploads llama_context: constructing llama_context llama_context: n_seq_max = 2 llama_context: n_ctx = 8192 llama_context: n_ctx_per_seq = 4096 llama_context: n_batch = 1024 llama_context: n_ubatch = 512 llama_context: causal_attn = 1 llama_context: flash_attn = 0 llama_context: freq_base = 1000000.0 llama_context: freq_scale = 1 llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized set_abort_callback: call llama_context: CUDA_Host output buffer size = 1.17 MiB create_memory: n_ctx = 8192 (padded) llama_kv_cache_unified: kv_size = 8192, type_k = 'f16', type_v = 'f16', n_layer = 48, can_shift = 1, padding = 32 llama_kv_cache_unified: layer 0: dev = CUDA0 llama_kv_cache_unified: layer 1: dev = CUDA0 llama_kv_cache_unified: layer 2: dev = CUDA0 llama_kv_cache_unified: layer 3: dev = CUDA0 llama_kv_cache_unified: layer 4: dev = CUDA0 llama_kv_cache_unified: layer 5: dev = CUDA0 llama_kv_cache_unified: layer 6: dev = CUDA0 llama_kv_cache_unified: layer 7: dev = CUDA0 llama_kv_cache_unified: layer 8: dev = CUDA0 llama_kv_cache_unified: layer 9: dev = CUDA0 llama_kv_cache_unified: layer 10: dev = CUDA0 llama_kv_cache_unified: layer 11: dev = CUDA0 llama_kv_cache_unified: layer 12: dev = CUDA0 llama_kv_cache_unified: layer 13: dev = CUDA0 llama_kv_cache_unified: layer 14: dev = CUDA0 llama_kv_cache_unified: layer 15: dev = CUDA0 llama_kv_cache_unified: layer 16: dev = CUDA0 llama_kv_cache_unified: layer 17: dev = CUDA0 llama_kv_cache_unified: layer 18: dev = CUDA0 llama_kv_cache_unified: layer 19: dev = CUDA0 llama_kv_cache_unified: layer 20: dev = CUDA0 llama_kv_cache_unified: layer 21: dev = CUDA0 llama_kv_cache_unified: layer 22: dev = CUDA0 llama_kv_cache_unified: layer 23: dev = CUDA0 llama_kv_cache_unified: layer 24: dev = CUDA0 llama_kv_cache_unified: layer 25: dev = CUDA0 llama_kv_cache_unified: layer 26: dev = CUDA0 llama_kv_cache_unified: layer 27: dev = CUDA0 llama_kv_cache_unified: layer 28: dev = CUDA0 llama_kv_cache_unified: layer 29: dev = CUDA0 llama_kv_cache_unified: layer 30: dev = CUDA0 llama_kv_cache_unified: layer 31: dev = CUDA0 llama_kv_cache_unified: layer 32: dev = CUDA0 llama_kv_cache_unified: layer 33: dev = CUDA0 llama_kv_cache_unified: layer 34: dev = CUDA0 llama_kv_cache_unified: layer 35: dev = CUDA0 llama_kv_cache_unified: layer 36: dev = CUDA0 llama_kv_cache_unified: layer 37: dev = CUDA0 llama_kv_cache_unified: layer 38: dev = CUDA0 llama_kv_cache_unified: layer 39: dev = CUDA0 llama_kv_cache_unified: layer 40: dev = CUDA0 llama_kv_cache_unified: layer 41: dev = CUDA0 llama_kv_cache_unified: layer 42: dev = CUDA0 llama_kv_cache_unified: layer 43: dev = CUDA0 llama_kv_cache_unified: layer 44: dev = CUDA0 llama_kv_cache_unified: layer 45: dev = CUDA0 llama_kv_cache_unified: layer 46: dev = CUDA0 llama_kv_cache_unified: layer 47: dev = CUDA0 llama_kv_cache_unified: CUDA0 KV buffer size = 768.00 MiB llama_kv_cache_unified: KV self size = 768.00 MiB, K (f16): 384.00 MiB, V (f16): 384.00 MiB llama_context: enumerating backends llama_context: backend_ptrs.size() = 2 llama_context: max_nodes = 65536 llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0 llama_context: reserving graph for n_tokens = 512, n_seqs = 1 llama_context: reserving graph for n_tokens = 1, n_seqs = 1 llama_context: reserving graph for n_tokens = 512, n_seqs = 1 llama_context: CUDA0 compute buffer size = 552.00 MiB llama_context: CUDA_Host compute buffer size = 20.01 MiB llama_context: graph nodes = 3126 llama_context: graph splits = 2 time=2025-06-06T21:48:49.065+08:00 level=INFO source=server.go:630 msg="llama runner started in 25.53 seconds" time=2025-06-06T21:48:49.065+08:00 level=DEBUG source=sched.go:495 msg="finished setting up" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2 time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=server.go:729 msg="completion request" images=0 prompt=104 format="" time=2025-06-06T21:48:49.090+08:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=30 used=0 remaining=30 [GIN] 2025/06/06 - 21:48:51 | 200 | 28.6746475s | 127.0.0.1 | POST "/v1/chat/completions" time=2025-06-06T21:48:51.995+08:00 level=DEBUG source=sched.go:503 msg="context for request finished" time=2025-06-06T21:48:51.996+08:00 level=DEBUG source=sched.go:343 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 duration=5m0s time=2025-06-06T21:48:51.996+08:00 level=DEBUG source=sched.go:361 msg="after processing request finished event" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 refCount=0 time=2025-06-06T21:53:52.004+08:00 level=DEBUG source=sched.go:345 msg="timer expired, expiring to unload" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 time=2025-06-06T21:53:52.004+08:00 level=DEBUG source=sched.go:364 msg="runner expired event received" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=sched.go:379 msg="got lock to unload expired event" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=sched.go:402 msg="starting background wait for VRAM recovery" runner.name=registry.ollama.ai/library/qwen3:30b runner.inference=cuda runner.devices=1 runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac runner.num_ctx=8192 time=2025-06-06T21:53:52.005+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="15.0 GiB" before.free_swap="22.9 GiB" now.total="31.6 GiB" now.free="16.8 GiB" now.free_swap="3.0 GiB" time=2025-06-06T21:53:52.021+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="29.7 GiB" now.total="31.8 GiB" now.free="10.6 GiB" now.used="21.3 GiB" releasing nvml library time=2025-06-06T21:53:52.039+08:00 level=DEBUG source=server.go:1023 msg="stopping llama server" pid=27056 time=2025-06-06T21:53:52.039+08:00 level=DEBUG source=server.go:1029 msg="waiting for llama server to exit" pid=27056 time=2025-06-06T21:53:52.164+08:00 level=DEBUG source=server.go:1033 msg="llama server stopped" pid=27056 time=2025-06-06T21:53:52.164+08:00 level=DEBUG source=sched.go:407 msg="runner terminated and removed from list, blocking for VRAM recovery" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac time=2025-06-06T21:53:52.272+08:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="31.6 GiB" before.free="16.8 GiB" before.free_swap="3.0 GiB" now.total="31.6 GiB" now.free="17.6 GiB" now.free_swap="23.5 GiB" time=2025-06-06T21:53:52.285+08:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-d2bc81d1-bd18-101d-0f21-85f4096fdc9f name="NVIDIA GeForce RTX 5090 D" overhead="0 B" before.total="31.8 GiB" before.free="10.6 GiB" now.total="31.8 GiB" now.free="29.6 GiB" now.used="2.2 GiB" releasing nvml library time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:700 msg="gpu VRAM free memory converged after 0.28 seconds" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:410 msg="sending an unloaded event" runner.size="19.8 GiB" runner.vram="19.8 GiB" runner.parallel=2 runner.pid=27056 runner.model=C:\Users\weihb\.ollama\models\blobs\sha256-e9183b5c18a0cf736578c1e3d1cbd4b7e98e3ad3be6176b68c20f156d54a07ac time=2025-06-06T21:53:52.286+08:00 level=DEBUG source=sched.go:312 msg="ignoring unload event with no pending requests"
GiteaMirror commented 2026-04-12 19:15:49 -05:00
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@rick-github commented on GitHub (Jun 6, 2025):

You have the default context length of 4096 tokens: OLLAMA_CONTEXT_LENGTH:4096.

time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2

The prompt is truncated, removing the system prompt.

Increase the context length.

<!-- gh-comment-id:2949368097 --> @rick-github commented on GitHub (Jun 6, 2025): You have the default context length of 4096 tokens: `OLLAMA_CONTEXT_LENGTH:4096`. ``` time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2 ``` The prompt is truncated, removing the system prompt. Increase the [context length](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-specify-the-context-window-size).
GiteaMirror commented 2026-04-12 19:15:49 -05:00
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@Harry-Up commented on GitHub (Jun 7, 2025):

You have the default context length of 4096 tokens: OLLAMA_CONTEXT_LENGTH:4096.

time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2

The prompt is truncated, removing the system prompt.

Increase the context length.

Thank you for your patient help. By increasing the context length, this problem was fixed. That helped me a lot.

<!-- gh-comment-id:2951409864 --> @Harry-Up commented on GitHub (Jun 7, 2025): > You have the default context length of 4096 tokens: `OLLAMA_CONTEXT_LENGTH:4096`. > > ``` > time=2025-06-06T21:48:49.088+08:00 level=DEBUG source=prompt.go:66 msg="truncating input messages which exceed context length" truncated=2 > ``` > > The prompt is truncated, removing the system prompt. > > Increase the [context length](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-specify-the-context-window-size). Thank you for your patient help. By increasing the context length, this problem was fixed. That helped me a lot.
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