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[GH-ISSUE #6669] Ubuntu GPU not used #4196

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opened 2026-04-12 15:07:42 -05:00 by GiteaMirror · 1 comment
GiteaMirror commented 2026-04-12 15:07:42 -05:00
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Originally created by @Andrii-suncor on GitHub (Sep 6, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/6669

What is the issue?

The GPU is not used when using

Start log

ollama start
2024/09/06 06:40:42 routes.go:1125: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/root/.ollama/models 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://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]"
time=2024-09-06T06:40:42.866Z level=INFO source=images.go:753 msg="total blobs: 5"
time=2024-09-06T06:40:42.867Z level=INFO source=images.go:760 msg="total unused blobs removed: 0"
time=2024-09-06T06:40:42.867Z level=INFO source=routes.go:1172 msg="Listening on 127.0.0.1:11434 (version 0.3.9)"
time=2024-09-06T06:40:42.867Z level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama3378081407/runners
time=2024-09-06T06:40:49.224Z level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cuda_v11 cuda_v12 rocm_v60102 cpu cpu_avx cpu_avx2]"
time=2024-09-06T06:40:49.224Z level=INFO source=gpu.go:200 msg="looking for compatible GPUs"
time=2024-09-06T06:40:49.224Z level=WARN source=gpu.go:222 msg="CPU does not have minimum vector extensions, GPU inference disabled" required=avx detected="no vector extensions"
time=2024-09-06T06:40:49.224Z level=INFO source=types.go:107 msg="inference compute" id=0 library=cpu variant="no vector extensions" compute="" driver=0.0 name="" total="40.2 GiB" available="39.2 GiB"
[GIN] 2024/09/06 - 06:41:19 | 200 |       22.99µs |       127.0.0.1 | HEAD     "/"
[GIN] 2024/09/06 - 06:41:19 | 200 |   13.003297ms |       127.0.0.1 | POST     "/api/show"
time=2024-09-06T06:41:19.646Z level=INFO source=memory.go:309 msg="offload to cpu" layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[39.2 GiB]" memory.required.full="5.8 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.8 GiB]" memory.weights.total="4.7 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="677.5 MiB"
time=2024-09-06T06:41:19.647Z level=INFO source=server.go:391 msg="starting llama server" cmd="/tmp/ollama3378081407/runners/cpu/ollama_llama_server --model /root/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe --ctx-size 8192 --batch-size 512 --embedding --log-disable --no-mmap --parallel 4 --port 45485"
time=2024-09-06T06:41:19.647Z level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2024-09-06T06:41:19.647Z level=INFO source=server.go:591 msg="waiting for llama runner to start responding"
time=2024-09-06T06:41:19.648Z level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error"
INFO [main] build info | build=1 commit="1e6f655" tid="137084946550976" timestamp=1725604879
INFO [main] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="137084946550976" timestamp=1725604879 total_threads=10
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="9" port="45485" tid="137084946550976" timestamp=1725604879
llama_model_loader: loaded meta data with 29 key-value pairs and 292 tensors from /root/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Meta Llama 3.1 8B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Meta-Llama-3.1
llama_model_loader: - kv   5:                         general.size_label str              = 8B
llama_model_loader: - kv   6:                            general.license str              = llama3.1
llama_model_loader: - kv   7:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   8:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   9:                          llama.block_count u32              = 32
llama_model_loader: - kv  10:                       llama.context_length u32              = 131072
llama_model_loader: - kv  11:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv  12:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv  13:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv  14:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  15:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  16:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  17:                          general.file_type u32              = 2
llama_model_loader: - kv  18:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  19:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  20:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  21:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  22:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  23:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  24:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  25:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  26:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  27:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  28:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   66 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
time=2024-09-06T06:41:19.899Z level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model"
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.7999 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 128256
llm_load_print_meta: n_merges         = 280147
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 131072
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 4
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale    = 0.0e+00
llm_load_print_meta: n_ff             = 14336
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 131072
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: ssm_d_conv       = 0
llm_load_print_meta: ssm_d_inner      = 0
llm_load_print_meta: ssm_d_state      = 0
llm_load_print_meta: ssm_dt_rank      = 0
llm_load_print_meta: model type       = 8B
llm_load_print_meta: model ftype      = Q4_0
llm_load_print_meta: model params     = 8.03 B
llm_load_print_meta: model size       = 4.33 GiB (4.64 BPW) 
llm_load_print_meta: general.name     = Meta Llama 3.1 8B Instruct
llm_load_print_meta: BOS token        = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token        = 128009 '<|eot_id|>'
llm_load_print_meta: LF token         = 128 'Ä'
llm_load_print_meta: EOT token        = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: ggml ctx size =    0.14 MiB
llm_load_tensors:        CPU buffer size =  4437.81 MiB
llama_new_context_with_model: n_ctx      = 8192
llama_new_context_with_model: n_batch    = 512
llama_new_context_with_model: n_ubatch   = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base  = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:        CPU KV buffer size =  1024.00 MiB
llama_new_context_with_model: KV self size  = 1024.00 MiB, K (f16):  512.00 MiB, V (f16):  512.00 MiB
llama_new_context_with_model:        CPU  output buffer size =     2.02 MiB
llama_new_context_with_model:        CPU compute buffer size =   560.01 MiB
llama_new_context_with_model: graph nodes  = 1030
llama_new_context_with_model: graph splits = 1
INFO [main] model loaded | tid="137084946550976" timestamp=1725604882
time=2024-09-06T06:41:22.659Z level=INFO source=server.go:630 msg="llama runner started in 3.01 seconds"
[GIN] 2024/09/06 - 06:41:22 | 200 |  3.048128204s |       127.0.0.1 | POST     "/api/chat"

nvidia-smi
image
nvtop
image
ollama ps
image
ollama -v
image

dmesg | grep -i nvrm
image
dmesg | grep -i nvidia
image

If additional information is needed, I can provide it later.

OS

Linux

GPU

Nvidia

CPU

AMD

Ollama version

0.3.9

Originally created by @Andrii-suncor on GitHub (Sep 6, 2024). Original GitHub issue: https://github.com/ollama/ollama/issues/6669 ### What is the issue? The GPU is not used when using Start log ``` ollama start 2024/09/06 06:40:42 routes.go:1125: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/root/.ollama/models 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://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" time=2024-09-06T06:40:42.866Z level=INFO source=images.go:753 msg="total blobs: 5" time=2024-09-06T06:40:42.867Z level=INFO source=images.go:760 msg="total unused blobs removed: 0" time=2024-09-06T06:40:42.867Z level=INFO source=routes.go:1172 msg="Listening on 127.0.0.1:11434 (version 0.3.9)" time=2024-09-06T06:40:42.867Z level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama3378081407/runners time=2024-09-06T06:40:49.224Z level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cuda_v11 cuda_v12 rocm_v60102 cpu cpu_avx cpu_avx2]" time=2024-09-06T06:40:49.224Z level=INFO source=gpu.go:200 msg="looking for compatible GPUs" time=2024-09-06T06:40:49.224Z level=WARN source=gpu.go:222 msg="CPU does not have minimum vector extensions, GPU inference disabled" required=avx detected="no vector extensions" time=2024-09-06T06:40:49.224Z level=INFO source=types.go:107 msg="inference compute" id=0 library=cpu variant="no vector extensions" compute="" driver=0.0 name="" total="40.2 GiB" available="39.2 GiB" [GIN] 2024/09/06 - 06:41:19 | 200 | 22.99µs | 127.0.0.1 | HEAD "/" [GIN] 2024/09/06 - 06:41:19 | 200 | 13.003297ms | 127.0.0.1 | POST "/api/show" time=2024-09-06T06:41:19.646Z level=INFO source=memory.go:309 msg="offload to cpu" layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[39.2 GiB]" memory.required.full="5.8 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.8 GiB]" memory.weights.total="4.7 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="677.5 MiB" time=2024-09-06T06:41:19.647Z level=INFO source=server.go:391 msg="starting llama server" cmd="/tmp/ollama3378081407/runners/cpu/ollama_llama_server --model /root/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe --ctx-size 8192 --batch-size 512 --embedding --log-disable --no-mmap --parallel 4 --port 45485" time=2024-09-06T06:41:19.647Z level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2024-09-06T06:41:19.647Z level=INFO source=server.go:591 msg="waiting for llama runner to start responding" time=2024-09-06T06:41:19.648Z level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server error" INFO [main] build info | build=1 commit="1e6f655" tid="137084946550976" timestamp=1725604879 INFO [main] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="137084946550976" timestamp=1725604879 total_threads=10 INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="9" port="45485" tid="137084946550976" timestamp=1725604879 llama_model_loader: loaded meta data with 29 key-value pairs and 292 tensors from /root/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = llama llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Meta Llama 3.1 8B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Meta-Llama-3.1 llama_model_loader: - kv 5: general.size_label str = 8B llama_model_loader: - kv 6: general.license str = llama3.1 llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam... llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ... llama_model_loader: - kv 9: llama.block_count u32 = 32 llama_model_loader: - kv 10: llama.context_length u32 = 131072 llama_model_loader: - kv 11: llama.embedding_length u32 = 4096 llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 13: llama.attention.head_count u32 = 32 llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000 llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 17: general.file_type u32 = 2 llama_model_loader: - kv 18: llama.vocab_size u32 = 128256 llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 21: tokenizer.ggml.pre str = llama-bpe llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000 llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009 llama_model_loader: - kv 27: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ... llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 66 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors time=2024-09-06T06:41:19.899Z level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model" llm_load_vocab: special tokens cache size = 256 llm_load_vocab: token to piece cache size = 0.7999 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = llama llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 128256 llm_load_print_meta: n_merges = 280147 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 131072 llm_load_print_meta: n_embd = 4096 llm_load_print_meta: n_layer = 32 llm_load_print_meta: n_head = 32 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_swa = 0 llm_load_print_meta: n_embd_head_k = 128 llm_load_print_meta: n_embd_head_v = 128 llm_load_print_meta: n_gqa = 4 llm_load_print_meta: n_embd_k_gqa = 1024 llm_load_print_meta: n_embd_v_gqa = 1024 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-05 llm_load_print_meta: f_clamp_kqv = 0.0e+00 llm_load_print_meta: f_max_alibi_bias = 0.0e+00 llm_load_print_meta: f_logit_scale = 0.0e+00 llm_load_print_meta: n_ff = 14336 llm_load_print_meta: n_expert = 0 llm_load_print_meta: n_expert_used = 0 llm_load_print_meta: causal attn = 1 llm_load_print_meta: pooling type = 0 llm_load_print_meta: rope type = 0 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 500000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 131072 llm_load_print_meta: rope_finetuned = unknown llm_load_print_meta: ssm_d_conv = 0 llm_load_print_meta: ssm_d_inner = 0 llm_load_print_meta: ssm_d_state = 0 llm_load_print_meta: ssm_dt_rank = 0 llm_load_print_meta: model type = 8B llm_load_print_meta: model ftype = Q4_0 llm_load_print_meta: model params = 8.03 B llm_load_print_meta: model size = 4.33 GiB (4.64 BPW) llm_load_print_meta: general.name = Meta Llama 3.1 8B Instruct llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>' llm_load_print_meta: EOS token = 128009 '<|eot_id|>' llm_load_print_meta: LF token = 128 'Ä' llm_load_print_meta: EOT token = 128009 '<|eot_id|>' llm_load_print_meta: max token length = 256 llm_load_tensors: ggml ctx size = 0.14 MiB llm_load_tensors: CPU buffer size = 4437.81 MiB llama_new_context_with_model: n_ctx = 8192 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 500000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CPU KV buffer size = 1024.00 MiB llama_new_context_with_model: KV self size = 1024.00 MiB, K (f16): 512.00 MiB, V (f16): 512.00 MiB llama_new_context_with_model: CPU output buffer size = 2.02 MiB llama_new_context_with_model: CPU compute buffer size = 560.01 MiB llama_new_context_with_model: graph nodes = 1030 llama_new_context_with_model: graph splits = 1 INFO [main] model loaded | tid="137084946550976" timestamp=1725604882 time=2024-09-06T06:41:22.659Z level=INFO source=server.go:630 msg="llama runner started in 3.01 seconds" [GIN] 2024/09/06 - 06:41:22 | 200 | 3.048128204s | 127.0.0.1 | POST "/api/chat" ``` nvidia-smi ![image](https://github.com/user-attachments/assets/b936a694-4ec0-47e2-9e9b-d609209373aa) nvtop ![image](https://github.com/user-attachments/assets/d5dc7a87-80aa-4cbc-a893-15fecf42bedd) ollama ps ![image](https://github.com/user-attachments/assets/f6f1c8ac-e29b-417d-b681-53db0db8f588) ollama -v ![image](https://github.com/user-attachments/assets/5139608d-37dd-4cea-9e45-090af903a816) dmesg | grep -i nvrm ![image](https://github.com/user-attachments/assets/56c5b4ad-97b1-4eaa-847c-a7e74651d4e0) dmesg | grep -i nvidia ![image](https://github.com/user-attachments/assets/17e1237e-609c-4968-a4be-3d1fe6f20bf0) If additional information is needed, I can provide it later. ### OS Linux ### GPU Nvidia ### CPU AMD ### Ollama version 0.3.9
GiteaMirror added the bug label 2026-04-12 15:07:42 -05:00
GiteaMirror commented 2026-04-12 15:07:44 -05:00
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@Andrii-suncor commented on GitHub (Sep 6, 2024):

Problem solved
The problem was in the CPU not support avx

<!-- gh-comment-id:2333461711 --> @Andrii-suncor commented on GitHub (Sep 6, 2024): Problem solved The problem was in the CPU not support avx
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