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[GH-ISSUE #11599] ollama run in docker, nvidia-smi not show running model process and ram usage, and it's slow #85342

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opened 2026-05-09 23:05:06 -05:00 by GiteaMirror · 7 comments
GiteaMirror commented 2026-05-09 23:05:06 -05:00
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Originally created by @lzzzzzzzzz on GitHub (Jul 31, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/11599

What is the issue?

root@28b2fab3e7f4:/# nvidia-smi
Thu Jul 31 08:32:16 2025
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100-PCIE... On | 00000000:00:0D.0 Off | 0 |
| N/A 38C P0 36W / 250W | 5038MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
root@28b2fab3e7f4:/# ollama ps
NAME ID SIZE PROCESSOR CONTEXT UNTIL
qwen3:14b bdbd181c33f2 10 GB 100% GPU 4096 45 seconds from now

and use postman to call /api/chat is two slow

Image

Relevant log output

OS

Linux

GPU

Nvidia

CPU

No response

Ollama version

No response

Originally created by @lzzzzzzzzz on GitHub (Jul 31, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/11599 ### What is the issue? root@28b2fab3e7f4:/# nvidia-smi Thu Jul 31 08:32:16 2025 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 Tesla V100-PCIE... On | 00000000:00:0D.0 Off | 0 | | N/A 38C P0 36W / 250W | 5038MiB / 32510MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| +-----------------------------------------------------------------------------+ root@28b2fab3e7f4:/# ollama ps NAME ID SIZE PROCESSOR CONTEXT UNTIL qwen3:14b bdbd181c33f2 10 GB 100% GPU 4096 45 seconds from now and use postman to call /api/chat is two slow <img width="1157" height="884" alt="Image" src="https://github.com/user-attachments/assets/989f5e54-19f9-42ff-a241-3a83e785cf49" /> ### Relevant log output ```shell ``` ### OS Linux ### GPU Nvidia ### CPU _No response_ ### Ollama version _No response_
GiteaMirror added the bugneeds more info labels 2026-05-09 23:05:06 -05:00
GiteaMirror commented 2026-05-09 23:05:12 -05:00
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@lzzzzzzzzz commented on GitHub (Jul 31, 2025):

image version: v0.10.1
gpu: Tesla V100
The additional 5G video memory used is occupied by the deployment of the Reknanker model in Xinference

Image
<!-- gh-comment-id:3139053707 --> @lzzzzzzzzz commented on GitHub (Jul 31, 2025): image version: v0.10.1 gpu: Tesla V100 The additional 5G video memory used is occupied by the deployment of the Reknanker model in Xinference <img width="822" height="467" alt="Image" src="https://github.com/user-attachments/assets/f5eda4d2-25f9-4eff-892a-cb59ade60f06" />
GiteaMirror commented 2026-05-09 23:05:13 -05:00
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@rick-github commented on GitHub (Jul 31, 2025):

Server logs may aid in debugging.

<!-- gh-comment-id:3139388097 --> @rick-github commented on GitHub (Jul 31, 2025): [Server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) may aid in debugging.
GiteaMirror commented 2026-05-09 23:05:15 -05:00
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@lzzzzzzzzz commented on GitHub (Aug 4, 2025):

Server logs may aid in debugging.

here is docker run logs

and call /api/chat use 10s
{
"model": "qwen3:14b",
"think": false,
"stream": false,
"messages": [
{
"role": "user",
"content": "hello!"
}
]
}
logs seems like use cpu not gpu,

here is the run_ollama_docker.sh
docker run -d --gpus=all -v ./.ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:latest

nvidia-smi
Mon Aug 4 11:19:35 2025
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100-PCIE... On | 00000000:00:0D.0 Off | 0 |
| N/A 36C P0 36W / 250W | 5036MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 25932 C Model: paraformer-zh-spk-0 2422MiB |
| 0 N/A N/A 32151 C Model: bge-reranker-v2-m3-0 2610MiB |
+-----------------------------------------------------------------------------+

[root@ecs-6f5e ollama]# ./run_ollama_docker.sh
92364580d527590493f6037c39d8500d14aba9fff0e66bd412e4a0c0ccc6a90c
[root@ecs-6f5e ollama]# docker logs ollama -f
time=2025-08-04T03:16:10.659Z level=INFO source=routes.go:1238 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:INFO 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:/root/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:1 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]"
time=2025-08-04T03:16:10.660Z level=INFO source=images.go:476 msg="total blobs: 18"
time=2025-08-04T03:16:10.660Z level=INFO source=images.go:483 msg="total unused blobs removed: 0"
time=2025-08-04T03:16:10.661Z level=INFO source=routes.go:1291 msg="Listening on [::]:11434 (version 0.10.1)"
time=2025-08-04T03:16:10.661Z level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-08-04T03:16:10.816Z level=WARN source=cuda_common.go:65 msg="old CUDA driver detected - please upgrade to a newer driver" version=11.4
time=2025-08-04T03:16:10.816Z level=INFO source=types.go:130 msg="inference compute" id=GPU-feddf176-ffeb-928f-5804-fb92c5d07371 library=cuda variant=v11 compute=7.0 driver=11.4 name="Tesla V100-PCIE-32GB" total="31.7 GiB" available="26.5 GiB"
time=2025-08-04T03:19:18.764Z level=INFO source=sched.go:786 msg="new model will fit in available VRAM in single GPU, loading" model=/root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e gpu=GPU-feddf176-ffeb-928f-5804-fb92c5d07371 parallel=1 available=28491382784 required="10.0 GiB"
time=2025-08-04T03:19:18.903Z level=INFO source=server.go:135 msg="system memory" total="62.8 GiB" free="40.3 GiB" free_swap="0 B"
time=2025-08-04T03:19:18.904Z level=INFO source=server.go:175 msg=offload library=cuda layers.requested=-1 layers.model=41 layers.offload=41 layers.split="" memory.available="[26.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.0 GiB" memory.required.partial="10.0 GiB" memory.required.kv="640.0 MiB" memory.required.allocations="[10.0 GiB]" memory.weights.total="8.2 GiB" memory.weights.repeating="7.6 GiB" memory.weights.nonrepeating="608.6 MiB" memory.graph.full="533.3 MiB" memory.graph.partial="533.3 MiB"
llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (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 = qwen3
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3 14B
llama_model_loader: - kv 3: general.basename str = Qwen3
llama_model_loader: - kv 4: general.size_label str = 14B
llama_model_loader: - kv 5: qwen3.block_count u32 = 40
llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120
llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408
llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40
llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - kv 26: general.file_type u32 = 15
llama_model_loader: - type f32: 161 tensors
llama_model_loader: - type f16: 40 tensors
llama_model_loader: - type q4_K: 221 tensors
llama_model_loader: - type q6_K: 21 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 8.63 GiB (5.02 BPW)
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3
print_info: vocab_only = 1
print_info: model type = ?B
print_info: model params = 14.77 B
print_info: general.name = Qwen3 14B
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=2025-08-04T03:19:19.187Z level=INFO source=server.go:438 msg="starting llama server" cmd="/usr/bin/ollama runner --model /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e --ctx-size 4096 --batch-size 512 --n-gpu-layers 41 --threads 4 --parallel 1 --port 45351"
time=2025-08-04T03:19:19.187Z level=INFO source=sched.go:481 msg="loaded runners" count=1
time=2025-08-04T03:19:19.187Z level=INFO source=server.go:598 msg="waiting for llama runner to start responding"
time=2025-08-04T03:19:19.188Z level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding"
time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner"
ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version
load_backend: loaded CUDA backend from /usr/lib/ollama/libggml-cuda.so
load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-skylakex.so
time=2025-08-04T03:19:19.294Z 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc)
time=2025-08-04T03:19:19.294Z level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:45351"
llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (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 = qwen3
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3 14B
llama_model_loader: - kv 3: general.basename str = Qwen3
llama_model_loader: - kv 4: general.size_label str = 14B
llama_model_loader: - kv 5: qwen3.block_count u32 = 40
llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120
llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408
llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40
llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - kv 26: general.file_type u32 = 15
llama_model_loader: - type f32: 161 tensors
llama_model_loader: - type f16: 40 tensors
llama_model_loader: - type q4_K: 221 tensors
llama_model_loader: - type q6_K: 21 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 8.63 GiB (5.02 BPW)
time=2025-08-04T03:19:19.439Z level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model"
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3
print_info: vocab_only = 0
print_info: n_ctx_train = 40960
print_info: n_embd = 5120
print_info: n_layer = 40
print_info: n_head = 40
print_info: n_head_kv = 8
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 = 5
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
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 = 17408
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 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 = 14B
print_info: model params = 14.77 B
print_info: general.name = Qwen3 14B
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 = true)
load_tensors: CPU_Mapped model buffer size = 8840.78 MiB
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch = 512
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
llama_context: CPU output buffer size = 0.60 MiB
llama_kv_cache_unified: kv_size = 4096, type_k = 'f16', type_v = 'f16', n_layer = 40, can_shift = 1, padding = 32
llama_kv_cache_unified: CPU KV buffer size = 640.00 MiB
llama_kv_cache_unified: KV self size = 640.00 MiB, K (f16): 320.00 MiB, V (f16): 320.00 MiB
llama_context: CPU compute buffer size = 368.01 MiB
llama_context: graph nodes = 1526
llama_context: graph splits = 1
time=2025-08-04T03:19:21.195Z level=INFO source=server.go:637 msg="llama runner started in 2.01 seconds"
[GIN] 2025/08/04 - 03:19:28 | 200 | 10.457950628s | 172.168.0.21 | POST "/api/chat"

<!-- gh-comment-id:3149009809 --> @lzzzzzzzzz commented on GitHub (Aug 4, 2025): > [Server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) may aid in debugging. here is docker run logs and call /api/chat use 10s { "model": "qwen3:14b", "think": false, "stream": false, "messages": [ { "role": "user", "content": "hello!" } ] } logs seems like use cpu not gpu, ----------------------------------- here is the run_ollama_docker.sh docker run -d --gpus=all -v ./.ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:latest ----------------------------------- nvidia-smi Mon Aug 4 11:19:35 2025 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 Tesla V100-PCIE... On | 00000000:00:0D.0 Off | 0 | | N/A 36C P0 36W / 250W | 5036MiB / 32510MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 25932 C Model: paraformer-zh-spk-0 2422MiB | | 0 N/A N/A 32151 C Model: bge-reranker-v2-m3-0 2610MiB | +-----------------------------------------------------------------------------+ ------------------------------------------------------- [root@ecs-6f5e ollama]# ./run_ollama_docker.sh 92364580d527590493f6037c39d8500d14aba9fff0e66bd412e4a0c0ccc6a90c [root@ecs-6f5e ollama]# docker logs ollama -f time=2025-08-04T03:16:10.659Z level=INFO source=routes.go:1238 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:INFO 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:/root/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:1 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]" time=2025-08-04T03:16:10.660Z level=INFO source=images.go:476 msg="total blobs: 18" time=2025-08-04T03:16:10.660Z level=INFO source=images.go:483 msg="total unused blobs removed: 0" time=2025-08-04T03:16:10.661Z level=INFO source=routes.go:1291 msg="Listening on [::]:11434 (version 0.10.1)" time=2025-08-04T03:16:10.661Z level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-08-04T03:16:10.816Z level=WARN source=cuda_common.go:65 msg="old CUDA driver detected - please upgrade to a newer driver" version=11.4 time=2025-08-04T03:16:10.816Z level=INFO source=types.go:130 msg="inference compute" id=GPU-feddf176-ffeb-928f-5804-fb92c5d07371 library=cuda variant=v11 compute=7.0 driver=11.4 name="Tesla V100-PCIE-32GB" total="31.7 GiB" available="26.5 GiB" time=2025-08-04T03:19:18.764Z level=INFO source=sched.go:786 msg="new model will fit in available VRAM in single GPU, loading" model=/root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e gpu=GPU-feddf176-ffeb-928f-5804-fb92c5d07371 parallel=1 available=28491382784 required="10.0 GiB" time=2025-08-04T03:19:18.903Z level=INFO source=server.go:135 msg="system memory" total="62.8 GiB" free="40.3 GiB" free_swap="0 B" time=2025-08-04T03:19:18.904Z level=INFO source=server.go:175 msg=offload library=cuda layers.requested=-1 layers.model=41 layers.offload=41 layers.split="" memory.available="[26.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.0 GiB" memory.required.partial="10.0 GiB" memory.required.kv="640.0 MiB" memory.required.allocations="[10.0 GiB]" memory.weights.total="8.2 GiB" memory.weights.repeating="7.6 GiB" memory.weights.nonrepeating="608.6 MiB" memory.graph.full="533.3 MiB" memory.graph.partial="533.3 MiB" llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (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 = qwen3 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen3 14B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 14B llama_model_loader: - kv 5: qwen3.block_count u32 = 40 llama_model_loader: - kv 6: qwen3.context_length u32 = 40960 llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120 llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408 llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40 llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 25: general.quantization_version u32 = 2 llama_model_loader: - kv 26: general.file_type u32 = 15 llama_model_loader: - type f32: 161 tensors llama_model_loader: - type f16: 40 tensors llama_model_loader: - type q4_K: 221 tensors llama_model_loader: - type q6_K: 21 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 8.63 GiB (5.02 BPW) load: special tokens cache size = 26 load: token to piece cache size = 0.9311 MB print_info: arch = qwen3 print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 14.77 B print_info: general.name = Qwen3 14B 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=2025-08-04T03:19:19.187Z level=INFO source=server.go:438 msg="starting llama server" cmd="/usr/bin/ollama runner --model /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e --ctx-size 4096 --batch-size 512 --n-gpu-layers 41 --threads 4 --parallel 1 --port 45351" time=2025-08-04T03:19:19.187Z level=INFO source=sched.go:481 msg="loaded runners" count=1 time=2025-08-04T03:19:19.187Z level=INFO source=server.go:598 msg="waiting for llama runner to start responding" time=2025-08-04T03:19:19.188Z level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding" time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner" ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version load_backend: loaded CUDA backend from /usr/lib/ollama/libggml-cuda.so load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-skylakex.so time=2025-08-04T03:19:19.294Z 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc) time=2025-08-04T03:19:19.294Z level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:45351" llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /root/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (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 = qwen3 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen3 14B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 14B llama_model_loader: - kv 5: qwen3.block_count u32 = 40 llama_model_loader: - kv 6: qwen3.context_length u32 = 40960 llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120 llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408 llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40 llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 25: general.quantization_version u32 = 2 llama_model_loader: - kv 26: general.file_type u32 = 15 llama_model_loader: - type f32: 161 tensors llama_model_loader: - type f16: 40 tensors llama_model_loader: - type q4_K: 221 tensors llama_model_loader: - type q6_K: 21 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 8.63 GiB (5.02 BPW) time=2025-08-04T03:19:19.439Z level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model" load: special tokens cache size = 26 load: token to piece cache size = 0.9311 MB print_info: arch = qwen3 print_info: vocab_only = 0 print_info: n_ctx_train = 40960 print_info: n_embd = 5120 print_info: n_layer = 40 print_info: n_head = 40 print_info: n_head_kv = 8 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 = 5 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 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 = 17408 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 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 = 14B print_info: model params = 14.77 B print_info: general.name = Qwen3 14B 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 = true) load_tensors: CPU_Mapped model buffer size = 8840.78 MiB llama_context: constructing llama_context llama_context: n_seq_max = 1 llama_context: n_ctx = 4096 llama_context: n_ctx_per_seq = 4096 llama_context: n_batch = 512 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 llama_context: CPU output buffer size = 0.60 MiB llama_kv_cache_unified: kv_size = 4096, type_k = 'f16', type_v = 'f16', n_layer = 40, can_shift = 1, padding = 32 llama_kv_cache_unified: CPU KV buffer size = 640.00 MiB llama_kv_cache_unified: KV self size = 640.00 MiB, K (f16): 320.00 MiB, V (f16): 320.00 MiB llama_context: CPU compute buffer size = 368.01 MiB llama_context: graph nodes = 1526 llama_context: graph splits = 1 time=2025-08-04T03:19:21.195Z level=INFO source=server.go:637 msg="llama runner started in 2.01 seconds" [GIN] 2025/08/04 - 03:19:28 | 200 | 10.457950628s | 172.168.0.21 | POST "/api/chat"
GiteaMirror commented 2026-05-09 23:05:18 -05:00
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@lzzzzzzzzz commented on GitHub (Aug 4, 2025):

I will try update NVIDIA-SMI driver, seem it's to old

<!-- gh-comment-id:3149014797 --> @lzzzzzzzzz commented on GitHub (Aug 4, 2025): I will try update NVIDIA-SMI driver, seem it's to old
GiteaMirror commented 2026-05-09 23:05:20 -05:00
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@rick-github commented on GitHub (Aug 4, 2025):

| NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 |

time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner"
ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version

Upgrade your Nvidia driver.

<!-- gh-comment-id:3149015440 --> @rick-github commented on GitHub (Aug 4, 2025): > | NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 | ``` time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner" ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version ``` Upgrade your Nvidia driver.
GiteaMirror commented 2026-05-09 23:05:22 -05:00
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@lzzzzzzzzz commented on GitHub (Aug 4, 2025):

| NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 |

time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner"
ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version

Upgrade your Nvidia driver.

it worked, thanks

<!-- gh-comment-id:3149149268 --> @lzzzzzzzzz commented on GitHub (Aug 4, 2025): > > | NVIDIA-SMI 470.223.02 Driver Version: 470.223.02 CUDA Version: 11.4 | > > ``` > time=2025-08-04T03:19:19.203Z level=INFO source=runner.go:815 msg="starting go runner" > ggml_cuda_init: failed to initialize CUDA: CUDA driver version is insufficient for CUDA runtime version > ``` > > Upgrade your Nvidia driver. it worked, thanks
GiteaMirror commented 2026-05-09 23:05:23 -05:00
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@gjhhust commented on GitHub (Aug 7, 2025):

I will try update NVIDIA-SMI driver, seem it's to old

我现在在 集群中的 docker 中，无法升级英伟达驱动，能用旧版来解决问题吗？或者其他方法

<!-- gh-comment-id:3162342939 --> @gjhhust commented on GitHub (Aug 7, 2025): > I will try update NVIDIA-SMI driver, seem it's to old 我现在在 集群中的 docker 中，无法升级英伟达驱动，能用旧版来解决问题吗？或者其他方法
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