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[GH-ISSUE #10687] GPU not used in dev mode #69084

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opened 2026-05-04 17:07:24 -05:00 by GiteaMirror · 4 comments
GiteaMirror commented 2026-05-04 17:07:24 -05:00
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Originally created by @AnouarTouati on GitHub (May 13, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/10687

What is the issue?

The binary release uses my Nvidia GPU, however when I cloned the repo ran it, my Nvidia GPU gets detected but not used, it runs on the CPU instead.

Relevant log output

C:\projects>cd ollama

C:\projects\ollama>go run . serve
time=2025-05-13T10:16:02.742-04:00 level=INFO source=routes.go:1230 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://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\Anouar\\.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=2025-05-13T10:16:02.745-04:00 level=INFO source=images.go:463 msg="total blobs: 9"
time=2025-05-13T10:16:02.746-04:00 level=INFO source=images.go:470 msg="total unused blobs removed: 0"
[GIN-debug] [WARNING] Creating an Engine instance with the Logger and Recovery middleware already attached.

[GIN-debug] [WARNING] Running in "debug" mode. Switch to "release" mode in production.
 - using env:   export GIN_MODE=release
 - using code:  gin.SetMode(gin.ReleaseMode)

[GIN-debug] HEAD   /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers)
[GIN-debug] GET    /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers)
[GIN-debug] HEAD   /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func3 (5 handlers)
[GIN-debug] GET    /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func4 (5 handlers)
[GIN-debug] POST   /api/pull                 --> github.com/ollama/ollama/server.(*Server).PullHandler-fm (5 handlers)
[GIN-debug] POST   /api/push                 --> github.com/ollama/ollama/server.(*Server).PushHandler-fm (5 handlers)
[GIN-debug] HEAD   /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers)
[GIN-debug] GET    /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers)
[GIN-debug] POST   /api/show                 --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (5 handlers)
[GIN-debug] DELETE /api/delete               --> github.com/ollama/ollama/server.(*Server).DeleteHandler-fm (5 handlers)
[GIN-debug] POST   /api/create               --> github.com/ollama/ollama/server.(*Server).CreateHandler-fm (5 handlers)
[GIN-debug] POST   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).CreateBlobHandler-fm (5 handlers)
[GIN-debug] HEAD   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).HeadBlobHandler-fm (5 handlers)
[GIN-debug] POST   /api/copy                 --> github.com/ollama/ollama/server.(*Server).CopyHandler-fm (5 handlers)
[GIN-debug] GET    /api/ps                   --> github.com/ollama/ollama/server.(*Server).PsHandler-fm (5 handlers)
[GIN-debug] POST   /api/generate             --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (5 handlers)
[GIN-debug] POST   /api/chat                 --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (5 handlers)
[GIN-debug] POST   /api/embed                --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (5 handlers)
[GIN-debug] POST   /api/embeddings           --> github.com/ollama/ollama/server.(*Server).EmbeddingsHandler-fm (5 handlers)
[GIN-debug] POST   /v1/chat/completions      --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers)
[GIN-debug] POST   /v1/completions           --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers)
[GIN-debug] POST   /v1/embeddings            --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers)
[GIN-debug] GET    /v1/models                --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (6 handlers)
[GIN-debug] GET    /v1/models/:model         --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (6 handlers)
time=2025-05-13T10:16:02.750-04:00 level=INFO source=routes.go:1283 msg="Listening on 127.0.0.1:11434 (version 0.0.0)"
time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:183 msg="efficiency cores detected" maxEfficiencyClass=1
time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=14 efficiency=8 threads=20
time=2025-05-13T10:16:02.867-04:00 level=INFO source=gpu.go:319 msg="detected OS VRAM overhead" id=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec library=cuda compute=8.6 driver=12.9 name="NVIDIA RTX A2000 8GB Laptop GPU" overhead="845.5 MiB"
time=2025-05-13T10:16:02.868-04:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec library=cuda variant=v12 compute=8.6 driver=12.9 name="NVIDIA RTX A2000 8GB Laptop GPU" total="8.0 GiB" available="7.0 GiB"
time=2025-05-13T10:16:57.736-04:00 level=INFO source=sched.go:776 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f gpu=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec parallel=1 available=7471112192 required="6.1 GiB"
time=2025-05-13T10:16:57.758-04:00 level=INFO source=server.go:135 msg="system memory" total="31.7 GiB" free="21.0 GiB" free_swap="24.5 GiB"
time=2025-05-13T10:16:57.763-04:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[7.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="6.1 GiB" memory.required.partial="6.1 GiB" memory.required.kv="576.0 MiB" memory.required.allocations="[6.1 GiB]" memory.weights.total="4.5 GiB" memory.weights.repeating="4.1 GiB" memory.weights.nonrepeating="486.9 MiB" memory.graph.full="384.0 MiB" memory.graph.partial="384.0 MiB"
llama_model_loader: loaded meta data with 28 key-value pairs and 399 tensors from C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f (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 8B
llama_model_loader: - kv   3:                           general.basename str              = Qwen3
llama_model_loader: - kv   4:                         general.size_label str              = 8B
llama_model_loader: - kv   5:                            general.license str              = apache-2.0
llama_model_loader: - kv   6:                          qwen3.block_count u32              = 36
llama_model_loader: - kv   7:                       qwen3.context_length u32              = 40960
llama_model_loader: - kv   8:                     qwen3.embedding_length u32              = 4096
llama_model_loader: - kv   9:                  qwen3.feed_forward_length u32              = 12288
llama_model_loader: - kv  10:                 qwen3.attention.head_count u32              = 32
llama_model_loader: - kv  11:              qwen3.attention.head_count_kv u32              = 8
llama_model_loader: - kv  12:                       qwen3.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  13:     qwen3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  14:                 qwen3.attention.key_length u32              = 128
llama_model_loader: - kv  15:               qwen3.attention.value_length u32              = 128
llama_model_loader: - kv  16:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  17:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  18:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  19:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  20:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  21:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  22:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  23:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  24:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  25:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  26:               general.quantization_version u32              = 2
llama_model_loader: - kv  27:                          general.file_type u32              = 15
llama_model_loader: - type  f32:  145 tensors
llama_model_loader: - type  f16:   36 tensors
llama_model_loader: - type q4_K:  199 tensors
llama_model_loader: - type q6_K:   19 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 4.86 GiB (5.10 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     = 8.19 B
print_info: general.name     = Qwen3 8B
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=2025-05-13T10:16:58.703-04:00 level=INFO source=server.go:431 msg="starting llama server" cmd="C:\\Users\\Anouar\\AppData\\Local\\go-build\\cb\\cbcf24ad2fad772f2c84a36c29bc58b9d5c4c77079740b7038bca182718c73d5-d\\ollama.exe runner --model C:\\Users\\Anouar\\.ollama\\models\\blobs\\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f --ctx-size 4096 --batch-size 512 --n-gpu-layers 37 --threads 6 --no-mmap --parallel 1 --port 51807"
time=2025-05-13T10:16:58.714-04:00 level=INFO source=sched.go:471 msg="loaded runners" count=1
time=2025-05-13T10:16:58.714-04:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding"
time=2025-05-13T10:16:58.716-04:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error"
time=2025-05-13T10:16:58.779-04:00 level=INFO source=runner.go:833 msg="starting go runner"
time=2025-05-13T10:16:58.781-04:00 level=INFO source=ggml.go:104 msg=system CPU.0.LLAMAFILE=1 compiler=cgo(gcc)
time=2025-05-13T10:16:58.785-04:00 level=INFO source=runner.go:892 msg="Server listening on 127.0.0.1:51807"
llama_model_loader: loaded meta data with 28 key-value pairs and 399 tensors from C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f (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 8B
llama_model_loader: - kv   3:                           general.basename str              = Qwen3
llama_model_loader: - kv   4:                         general.size_label str              = 8B
llama_model_loader: - kv   5:                            general.license str              = apache-2.0
llama_model_loader: - kv   6:                          qwen3.block_count u32              = 36
llama_model_loader: - kv   7:                       qwen3.context_length u32              = 40960
llama_model_loader: - kv   8:                     qwen3.embedding_length u32              = 4096
llama_model_loader: - kv   9:                  qwen3.feed_forward_length u32              = 12288
llama_model_loader: - kv  10:                 qwen3.attention.head_count u32              = 32
llama_model_loader: - kv  11:              qwen3.attention.head_count_kv u32              = 8
llama_model_loader: - kv  12:                       qwen3.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  13:     qwen3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  14:                 qwen3.attention.key_length u32              = 128
llama_model_loader: - kv  15:               qwen3.attention.value_length u32              = 128
llama_model_loader: - kv  16:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  17:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  18:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  19:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  20:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  21:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  22:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  23:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  24:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  25:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  26:               general.quantization_version u32              = 2
llama_model_loader: - kv  27:                          general.file_type u32              = 15
llama_model_loader: - type  f32:  145 tensors
llama_model_loader: - type  f16:   36 tensors
llama_model_loader: - type q4_K:  199 tensors
llama_model_loader: - type q6_K:   19 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 4.86 GiB (5.10 BPW)
load: special tokens cache size = 26
time=2025-05-13T10:16:58.968-04:00 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             = qwen3
print_info: vocab_only       = 0
print_info: n_ctx_train      = 40960
print_info: n_embd           = 4096
print_info: n_layer          = 36
print_info: n_head           = 32
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            = 4
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             = 12288
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       = 8B
print_info: model params     = 8.19 B
print_info: general.name     = Qwen3 8B
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:          CPU model buffer size =  4977.62 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 = 36, can_shift = 1, padding = 32
llama_kv_cache_unified:        CPU KV buffer size =   576.00 MiB
llama_kv_cache_unified: KV self size  =  576.00 MiB, K (f16):  288.00 MiB, V (f16):  288.00 MiB
llama_context:        CPU compute buffer size =   304.75 MiB
llama_context: graph nodes  = 1374
llama_context: graph splits = 1
time=2025-05-13T10:17:00.978-04:00 level=INFO source=server.go:630 msg="llama runner started in 2.26 seconds"
[GIN] 2025/05/13 - 10:22:56 | 200 |         5m59s |       127.0.0.1 | POST     "/api/generate"

OS

Win 11

GPU

RTX A2000 8GB

CPU

I7 12800H

Ollama version

Latest commit on main branch

Originally created by @AnouarTouati on GitHub (May 13, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/10687 ### What is the issue? The binary release uses my Nvidia GPU, however when I cloned the repo ran it, my Nvidia GPU gets detected but not used, it runs on the CPU instead. ### Relevant log output ```shell C:\projects>cd ollama C:\projects\ollama>go run . serve time=2025-05-13T10:16:02.742-04:00 level=INFO source=routes.go:1230 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://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\Anouar\\.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=2025-05-13T10:16:02.745-04:00 level=INFO source=images.go:463 msg="total blobs: 9" time=2025-05-13T10:16:02.746-04:00 level=INFO source=images.go:470 msg="total unused blobs removed: 0" [GIN-debug] [WARNING] Creating an Engine instance with the Logger and Recovery middleware already attached. [GIN-debug] [WARNING] Running in "debug" mode. Switch to "release" mode in production. - using env: export GIN_MODE=release - using code: gin.SetMode(gin.ReleaseMode) [GIN-debug] HEAD / --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers) [GIN-debug] GET / --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers) [GIN-debug] HEAD /api/version --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func3 (5 handlers) [GIN-debug] GET /api/version --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func4 (5 handlers) [GIN-debug] POST /api/pull --> github.com/ollama/ollama/server.(*Server).PullHandler-fm (5 handlers) [GIN-debug] POST /api/push --> github.com/ollama/ollama/server.(*Server).PushHandler-fm (5 handlers) [GIN-debug] HEAD /api/tags --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers) [GIN-debug] GET /api/tags --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers) [GIN-debug] POST /api/show --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (5 handlers) [GIN-debug] DELETE /api/delete --> github.com/ollama/ollama/server.(*Server).DeleteHandler-fm (5 handlers) [GIN-debug] POST /api/create --> github.com/ollama/ollama/server.(*Server).CreateHandler-fm (5 handlers) [GIN-debug] POST /api/blobs/:digest --> github.com/ollama/ollama/server.(*Server).CreateBlobHandler-fm (5 handlers) [GIN-debug] HEAD /api/blobs/:digest --> github.com/ollama/ollama/server.(*Server).HeadBlobHandler-fm (5 handlers) [GIN-debug] POST /api/copy --> github.com/ollama/ollama/server.(*Server).CopyHandler-fm (5 handlers) [GIN-debug] GET /api/ps --> github.com/ollama/ollama/server.(*Server).PsHandler-fm (5 handlers) [GIN-debug] POST /api/generate --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (5 handlers) [GIN-debug] POST /api/chat --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (5 handlers) [GIN-debug] POST /api/embed --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (5 handlers) [GIN-debug] POST /api/embeddings --> github.com/ollama/ollama/server.(*Server).EmbeddingsHandler-fm (5 handlers) [GIN-debug] POST /v1/chat/completions --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers) [GIN-debug] POST /v1/completions --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers) [GIN-debug] POST /v1/embeddings --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers) [GIN-debug] GET /v1/models --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (6 handlers) [GIN-debug] GET /v1/models/:model --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (6 handlers) time=2025-05-13T10:16:02.750-04:00 level=INFO source=routes.go:1283 msg="Listening on 127.0.0.1:11434 (version 0.0.0)" time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:183 msg="efficiency cores detected" maxEfficiencyClass=1 time=2025-05-13T10:16:02.750-04:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=14 efficiency=8 threads=20 time=2025-05-13T10:16:02.867-04:00 level=INFO source=gpu.go:319 msg="detected OS VRAM overhead" id=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec library=cuda compute=8.6 driver=12.9 name="NVIDIA RTX A2000 8GB Laptop GPU" overhead="845.5 MiB" time=2025-05-13T10:16:02.868-04:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec library=cuda variant=v12 compute=8.6 driver=12.9 name="NVIDIA RTX A2000 8GB Laptop GPU" total="8.0 GiB" available="7.0 GiB" time=2025-05-13T10:16:57.736-04:00 level=INFO source=sched.go:776 msg="new model will fit in available VRAM in single GPU, loading" model=C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f gpu=GPU-73366d3f-bfc0-96ea-75fb-2a6f08fdccec parallel=1 available=7471112192 required="6.1 GiB" time=2025-05-13T10:16:57.758-04:00 level=INFO source=server.go:135 msg="system memory" total="31.7 GiB" free="21.0 GiB" free_swap="24.5 GiB" time=2025-05-13T10:16:57.763-04:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[7.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="6.1 GiB" memory.required.partial="6.1 GiB" memory.required.kv="576.0 MiB" memory.required.allocations="[6.1 GiB]" memory.weights.total="4.5 GiB" memory.weights.repeating="4.1 GiB" memory.weights.nonrepeating="486.9 MiB" memory.graph.full="384.0 MiB" memory.graph.partial="384.0 MiB" llama_model_loader: loaded meta data with 28 key-value pairs and 399 tensors from C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f (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 8B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 8B llama_model_loader: - kv 5: general.license str = apache-2.0 llama_model_loader: - kv 6: qwen3.block_count u32 = 36 llama_model_loader: - kv 7: qwen3.context_length u32 = 40960 llama_model_loader: - kv 8: qwen3.embedding_length u32 = 4096 llama_model_loader: - kv 9: qwen3.feed_forward_length u32 = 12288 llama_model_loader: - kv 10: qwen3.attention.head_count u32 = 32 llama_model_loader: - kv 11: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 12: qwen3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 13: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 14: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 15: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 16: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 17: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 18: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 20: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 22: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 23: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 25: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 26: general.quantization_version u32 = 2 llama_model_loader: - kv 27: general.file_type u32 = 15 llama_model_loader: - type f32: 145 tensors llama_model_loader: - type f16: 36 tensors llama_model_loader: - type q4_K: 199 tensors llama_model_loader: - type q6_K: 19 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 4.86 GiB (5.10 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 = 8.19 B print_info: general.name = Qwen3 8B 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=2025-05-13T10:16:58.703-04:00 level=INFO source=server.go:431 msg="starting llama server" cmd="C:\\Users\\Anouar\\AppData\\Local\\go-build\\cb\\cbcf24ad2fad772f2c84a36c29bc58b9d5c4c77079740b7038bca182718c73d5-d\\ollama.exe runner --model C:\\Users\\Anouar\\.ollama\\models\\blobs\\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f --ctx-size 4096 --batch-size 512 --n-gpu-layers 37 --threads 6 --no-mmap --parallel 1 --port 51807" time=2025-05-13T10:16:58.714-04:00 level=INFO source=sched.go:471 msg="loaded runners" count=1 time=2025-05-13T10:16:58.714-04:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding" time=2025-05-13T10:16:58.716-04:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error" time=2025-05-13T10:16:58.779-04:00 level=INFO source=runner.go:833 msg="starting go runner" time=2025-05-13T10:16:58.781-04:00 level=INFO source=ggml.go:104 msg=system CPU.0.LLAMAFILE=1 compiler=cgo(gcc) time=2025-05-13T10:16:58.785-04:00 level=INFO source=runner.go:892 msg="Server listening on 127.0.0.1:51807" llama_model_loader: loaded meta data with 28 key-value pairs and 399 tensors from C:\Users\Anouar\.ollama\models\blobs\sha256-a3de86cd1c132c822487ededd47a324c50491393e6565cd14bafa40d0b8e686f (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 8B llama_model_loader: - kv 3: general.basename str = Qwen3 llama_model_loader: - kv 4: general.size_label str = 8B llama_model_loader: - kv 5: general.license str = apache-2.0 llama_model_loader: - kv 6: qwen3.block_count u32 = 36 llama_model_loader: - kv 7: qwen3.context_length u32 = 40960 llama_model_loader: - kv 8: qwen3.embedding_length u32 = 4096 llama_model_loader: - kv 9: qwen3.feed_forward_length u32 = 12288 llama_model_loader: - kv 10: qwen3.attention.head_count u32 = 32 llama_model_loader: - kv 11: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 12: qwen3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 13: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 14: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 15: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 16: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 17: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 18: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 20: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 22: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 23: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 25: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 26: general.quantization_version u32 = 2 llama_model_loader: - kv 27: general.file_type u32 = 15 llama_model_loader: - type f32: 145 tensors llama_model_loader: - type f16: 36 tensors llama_model_loader: - type q4_K: 199 tensors llama_model_loader: - type q6_K: 19 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 4.86 GiB (5.10 BPW) load: special tokens cache size = 26 time=2025-05-13T10:16:58.968-04:00 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 = qwen3 print_info: vocab_only = 0 print_info: n_ctx_train = 40960 print_info: n_embd = 4096 print_info: n_layer = 36 print_info: n_head = 32 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 = 4 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 = 12288 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 = 8B print_info: model params = 8.19 B print_info: general.name = Qwen3 8B 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: CPU model buffer size = 4977.62 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 = 36, can_shift = 1, padding = 32 llama_kv_cache_unified: CPU KV buffer size = 576.00 MiB llama_kv_cache_unified: KV self size = 576.00 MiB, K (f16): 288.00 MiB, V (f16): 288.00 MiB llama_context: CPU compute buffer size = 304.75 MiB llama_context: graph nodes = 1374 llama_context: graph splits = 1 time=2025-05-13T10:17:00.978-04:00 level=INFO source=server.go:630 msg="llama runner started in 2.26 seconds" [GIN] 2025/05/13 - 10:22:56 | 200 | 5m59s | 127.0.0.1 | POST "/api/generate" ``` ### OS _Win 11_ ### GPU _RTX A2000 8GB_ ### CPU _I7 12800H_ ### Ollama version _Latest commit on main branch_
GiteaMirror added the bug label 2026-05-04 17:07:24 -05:00
GiteaMirror commented 2026-05-04 17:07:28 -05:00
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@rick-github commented on GitHub (May 13, 2025):

Did you build the runners?

<!-- gh-comment-id:2876865125 --> @rick-github commented on GitHub (May 13, 2025): Did you build the runners?
GiteaMirror commented 2026-05-04 17:07:30 -05:00
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@AnouarTouati commented on GitHub (May 13, 2025):

I just followed the steps here Docs
I am new to the repo, I dont know what runners are.

<!-- gh-comment-id:2876878590 --> @AnouarTouati commented on GitHub (May 13, 2025): I just followed the steps here [Docs](https://github.com/ollama/ollama/blob/main/docs/development.md) I am new to the repo, I dont know what runners are.
GiteaMirror commented 2026-05-04 17:07:31 -05:00
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@rick-github commented on GitHub (May 13, 2025):

https://github.com/ollama/ollama/blob/main/docs/development.md#windows

cmake -B build
cmake --build build --config Release
<!-- gh-comment-id:2876886325 --> @rick-github commented on GitHub (May 13, 2025): https://github.com/ollama/ollama/blob/main/docs/development.md#windows ``` cmake -B build cmake --build build --config Release ```
GiteaMirror commented 2026-05-04 17:07:33 -05:00
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@AnouarTouati commented on GitHub (May 13, 2025):

I saw the go run . serve and assumed it was all I had to do because it said 'serve'.
Thank you for pointing the other steps.

<!-- gh-comment-id:2876934011 --> @AnouarTouati commented on GitHub (May 13, 2025): I saw the `go run . serve` and assumed it was all I had to do because it said 'serve'. Thank you for pointing the other steps.
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Reference: github-starred/ollama#69084
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