[GH-ISSUE #12586] ollama ps shows 100% GPU but the GPU is not utilized #8352

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opened 2026-04-12 20:57:08 -05:00 by GiteaMirror · 1 comment

GiteaMirror commented 2026-04-12 20:57:08 -05:00

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Originally created by @thomek on GitHub (Oct 12, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/12586

What is the issue?

I'm running

ollama run llama3:8b "Explain machine learning in simple terms"

ollama ps shows 100% GPU but the GPU is actually not utilized according to nvidia-smi.

The log indicates that Ollama recognizes the GPU. But it does not load a GPU backend:

Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650
Okt 12 10:43:11 airblast ollama[83240]: calling cuInit
Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion
Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8
Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0
Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount
Okt 12 10:43:11 airblast ollama[83240]: device count 1
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=INFO source=runner.go:864 msg="starting go runner"
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/lib/ollama
Okt 12 10:43:11 airblast ollama[83240]: operator() double registration of ggml_uncaught_exception
Okt 12 10:43:11 airblast ollama[83240]: load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc)
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=runner.go:900 msg="Server listening on 127.0.0.1:40323"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB"
Okt 12 10:43:12 airblast ollama[83240]: releasing cuda driver library

I'm using OpenSUSE Tumbleweed version 20251007. The Ollama version is 0.12.3 (according to zypper, ollama --version says 0.0.0).

I scanned the lasted issues reported on GitHub but was not able to solve the issue myself. Thank you very much for your help if you should find the time to have a look at my problem!

Relevant log output

ollama ps



NAME         ID              SIZE      PROCESSOR    CONTEXT    UNTIL              
llama3:8b    365c0bd3c000    5.8 GB    100% GPU     4096       4 minutes from now 



nvidia-smi



Sun Oct 12 10:43:20 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05              Driver Version: 580.95.05      CUDA Version: 13.0     |
+-----------------------------------------+------------------------+----------------------+
| 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  NVIDIA GeForce RTX 4080 ...    On  |   00000000:01:00.0  On |                  N/A |
| N/A   45C    P8              3W /  175W |     137MiB /  12282MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A            2352      G   /usr/bin/Xorg.bin                        58MiB |
|    0   N/A  N/A            2630      G   /usr/bin/kwin_wayland                     3MiB |
+-----------------------------------------------------------------------------------------+



journalctl -u ollama --since '2025-10-12 10:43:00' --no-pager



Okt 12 10:43:02 airblast systemd[1]: Stopping Ollama Service...
Okt 12 10:43:02 airblast systemd[1]: ollama.service: Deactivated successfully.
Okt 12 10:43:02 airblast systemd[1]: Stopped Ollama Service.
Okt 12 10:43:02 airblast systemd[1]: ollama.service: Consumed 5min 10.842s CPU time.
Okt 12 10:43:02 airblast systemd[1]: Started Ollama Service.
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.499+02:00 level=INFO source=routes.go:1475 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:4096 OLLAMA_DEBUG:DEBUG OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE:f16 OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/var/lib/ollama/.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_REMOTES:[ollama.com] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.500+02:00 level=INFO source=images.go:518 msg="total blobs: 33"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.501+02:00 level=INFO source=images.go:525 msg="total unused blobs removed: 0"
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] [WARNING] Creating an Engine instance with the Logger and Recovery middleware already attached.
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] [WARNING] Running in "debug" mode. Switch to "release" mode in production.
Okt 12 10:43:02 airblast ollama[83240]:  - using env:        export GIN_MODE=release
Okt 12 10:43:02 airblast ollama[83240]:  - using code:        gin.SetMode(gin.ReleaseMode)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD   /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /                         --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD   /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func3 (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /api/version              --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func4 (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/pull                 --> github.com/ollama/ollama/server.(*Server).PullHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/push                 --> github.com/ollama/ollama/server.(*Server).PushHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD   /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /api/tags                 --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/show                 --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] DELETE /api/delete               --> github.com/ollama/ollama/server.(*Server).DeleteHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/me                   --> github.com/ollama/ollama/server.(*Server).WhoamiHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/signout              --> github.com/ollama/ollama/server.(*Server).SignoutHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] DELETE /api/user/keys/:encodedKey --> github.com/ollama/ollama/server.(*Server).SignoutHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/create               --> github.com/ollama/ollama/server.(*Server).CreateHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).CreateBlobHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD   /api/blobs/:digest        --> github.com/ollama/ollama/server.(*Server).HeadBlobHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/copy                 --> github.com/ollama/ollama/server.(*Server).CopyHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /api/ps                   --> github.com/ollama/ollama/server.(*Server).PsHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/generate             --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/chat                 --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/embed                --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /api/embeddings           --> github.com/ollama/ollama/server.(*Server).EmbeddingsHandler-fm (5 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /v1/chat/completions      --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /v1/completions           --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST   /v1/embeddings            --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /v1/models                --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (6 handlers)
Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET    /v1/models/:model         --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (6 handlers)
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=INFO source=routes.go:1528 msg="Listening on 127.0.0.1:11434 (version 0.0.0)"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=DEBUG source=sched.go:121 msg="starting llm scheduler"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:98 msg="searching for GPU discovery libraries for NVIDIA"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:520 msg="Searching for GPU library" name=libcuda.so*
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:544 msg="gpu library search" globs="[/usr/lib/ollama/libcuda.so* /libcuda.so* /usr/local/cuda*/targets/*/lib/libcuda.so* /usr/lib/*-linux-gnu/nvidia/current/libcuda.so* /usr/lib/*-linux-gnu/libcuda.so* /usr/lib/wsl/lib/libcuda.so* /usr/lib/wsl/drivers/*/libcuda.so* /opt/cuda/lib*/libcuda.so* /usr/local/cuda/lib*/libcuda.so* /usr/lib*/libcuda.so* /usr/local/lib*/libcuda.so*]"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.505+02:00 level=DEBUG source=gpu.go:577 msg="discovered GPU libraries" paths=[/usr/lib64/libcuda.so.580.95.05]
Okt 12 10:43:02 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460
Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650
Okt 12 10:43:02 airblast ollama[83240]: calling cuInit
Okt 12 10:43:02 airblast ollama[83240]: calling cuDriverGetVersion
Okt 12 10:43:02 airblast ollama[83240]: raw version 0x32c8
Okt 12 10:43:02 airblast ollama[83240]: CUDA driver version: 13.0
Okt 12 10:43:02 airblast ollama[83240]: calling cuDeviceGetCount
Okt 12 10:43:02 airblast ollama[83240]: device count 1
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.616+02:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=/usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] CUDA totalMem 11874mb
Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] CUDA freeMem 11546mb
Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] Compute Capability 8.9
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=DEBUG source=amd_linux.go:423 msg="amdgpu driver not detected /sys/module/amdgpu"
Okt 12 10:43:02 airblast ollama[83240]: releasing cuda driver library
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=INFO source=types.go:131 msg="inference compute" id=GPU-00974eaa-b009-056b-5f0e-05794f5f125c library=cuda variant=v13 compute=8.9 driver=13.0 name="NVIDIA GeForce RTX 4080 Laptop GPU" total="11.6 GiB" available="11.3 GiB"
Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=INFO source=routes.go:1569 msg="entering low vram mode" "total vram"="11.6 GiB" threshold="20.0 GiB"
Okt 12 10:43:11 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:11 | 200 |      24.247µs |       127.0.0.1 | HEAD     "/"
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.524+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=general.alignment default=32
Okt 12 10:43:11 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:11 | 200 |   48.541925ms |       127.0.0.1 | POST     "/api/show"
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.588+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.4 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.3 GiB" now.free_swap="96.0 GiB"
Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650
Okt 12 10:43:11 airblast ollama[83240]: calling cuInit
Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion
Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8
Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0
Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount
Okt 12 10:43:11 airblast ollama[83240]: device count 1
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.690+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB"
Okt 12 10:43:11 airblast ollama[83240]: releasing cuda driver library
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.690+02:00 level=DEBUG source=sched.go:188 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.698+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=general.alignment default=32
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.698+02:00 level=DEBUG source=sched.go:208 msg="loading first model" model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa (version GGUF V3 (latest))
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   0:                       general.architecture str              = llama
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   1:                               general.name str              = Meta-Llama-3-8B-Instruct
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   2:                          llama.block_count u32              = 32
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   3:                       llama.context_length u32              = 8192
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 500000.000000
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  10:                          general.file_type u32              = 2
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  11:                           llama.vocab_size u32              = 128256
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = gpt2
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = llama-bpe
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  16:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  17:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 128000
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 128009
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  20:                    tokenizer.chat_template str              = {% set loop_messages = messages %}{% ...
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv  21:               general.quantization_version u32              = 2
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type  f32:   65 tensors
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type q4_0:  225 tensors
Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type q6_K:    1 tensors
Okt 12 10:43:11 airblast ollama[83240]: print_info: file format = GGUF V3 (latest)
Okt 12 10:43:11 airblast ollama[83240]: print_info: file type   = Q4_0
Okt 12 10:43:11 airblast ollama[83240]: print_info: file size   = 4.33 GiB (4.64 BPW)
Okt 12 10:43:11 airblast ollama[83240]: init_tokenizer: initializing tokenizer for type 2
Okt 12 10:43:11 airblast ollama[83240]: load: control token: 128255 '<|reserved_special_token_250|>' is not marked as EOG
...
Okt 12 10:43:11 airblast ollama[83240]: load: control token: 128123 '<|reserved_special_token_118|>' is not marked as EOG
Okt 12 10:43:11 airblast ollama[83240]: load: printing all EOG tokens:
Okt 12 10:43:11 airblast ollama[83240]: load:   - 128001 ('<|end_of_text|>')
Okt 12 10:43:11 airblast ollama[83240]: load:   - 128009 ('<|eot_id|>')
Okt 12 10:43:11 airblast ollama[83240]: load: special tokens cache size = 256
Okt 12 10:43:11 airblast ollama[83240]: load: token to piece cache size = 0.8000 MB
Okt 12 10:43:11 airblast ollama[83240]: print_info: arch             = llama
Okt 12 10:43:11 airblast ollama[83240]: print_info: vocab_only       = 1
Okt 12 10:43:11 airblast ollama[83240]: print_info: model type       = ?B
Okt 12 10:43:11 airblast ollama[83240]: print_info: model params     = 8.03 B
Okt 12 10:43:11 airblast ollama[83240]: print_info: general.name     = Meta-Llama-3-8B-Instruct
Okt 12 10:43:11 airblast ollama[83240]: print_info: vocab type       = BPE
Okt 12 10:43:11 airblast ollama[83240]: print_info: n_vocab          = 128256
Okt 12 10:43:11 airblast ollama[83240]: print_info: n_merges         = 280147
Okt 12 10:43:11 airblast ollama[83240]: print_info: BOS token        = 128000 '<|begin_of_text|>'
Okt 12 10:43:11 airblast ollama[83240]: print_info: EOS token        = 128009 '<|eot_id|>'
Okt 12 10:43:11 airblast ollama[83240]: print_info: EOT token        = 128009 '<|eot_id|>'
Okt 12 10:43:11 airblast ollama[83240]: print_info: LF token         = 198 'Ċ'
Okt 12 10:43:11 airblast ollama[83240]: print_info: EOG token        = 128001 '<|end_of_text|>'
Okt 12 10:43:11 airblast ollama[83240]: print_info: EOG token        = 128009 '<|eot_id|>'
Okt 12 10:43:11 airblast ollama[83240]: print_info: max token length = 256
Okt 12 10:43:11 airblast ollama[83240]: llama_model_load: vocab only - skipping tensors
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.855+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.3 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.2 GiB" now.free_swap="96.0 GiB"
Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650
Okt 12 10:43:11 airblast ollama[83240]: calling cuInit
Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion
Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8
Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0
Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount
Okt 12 10:43:11 airblast ollama[83240]: device count 1
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB"
Okt 12 10:43:11 airblast ollama[83240]: releasing cuda driver library
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=INFO source=server.go:399 msg="starting runner" cmd="/usr/bin/ollama runner --model /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa --port 40323"
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=DEBUG source=server.go:400 msg=subprocess PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin OLLAMA_DEBUG=1 OLLAMA_LOG_LEVEL=debug OLLAMA_HOST=http://127.0.0.1:11434 OLLAMA_KV_CACHE_TYPE=f16 OLLAMA_KEEP_ALIVE="" OLLAMA_NUM_PARALLEL="" OLLAMA_MAX_VRAM="" OLLAMA_RUNNERS_DIR="" OLLAMA_TMPDIR="" OLLAMA_MODELS="" OLLAMA_ORIGINS="" OLLAMA_MAX_LOADED_MODELS=3 OLLAMA_LIBRARY_PATH=/usr/lib/ollama LD_LIBRARY_PATH=/usr/lib/ollama:/usr/lib/ollama
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.946+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.2 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.2 GiB" now.free_swap="96.0 GiB"
Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460
Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650
Okt 12 10:43:11 airblast ollama[83240]: calling cuInit
Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion
Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8
Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0
Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount
Okt 12 10:43:11 airblast ollama[83240]: device count 1
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=INFO source=runner.go:864 msg="starting go runner"
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/lib/ollama
Okt 12 10:43:11 airblast ollama[83240]: operator() double registration of ggml_uncaught_exception
Okt 12 10:43:11 airblast ollama[83240]: load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc)
Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=runner.go:900 msg="Server listening on 127.0.0.1:40323"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB"
Okt 12 10:43:12 airblast ollama[83240]: releasing cuda driver library
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=INFO source=server.go:504 msg="system memory" total="62.5 GiB" free="57.2 GiB" free_swap="96.0 GiB"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=memory.go:181 msg=evaluating library=cuda gpu_count=1 available="[11.3 GiB]"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.vision.block_count default=0
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.key_length default=128
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.value_length default=128
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:611 msg="default cache size estimate" "attention MiB"=512 "attention bytes"=536870912 "recurrent MiB"=0 "recurrent bytes"=0
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=memory.go:36 msg="new model will fit in available VRAM across minimum required GPUs, loading" model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa library=cuda parallel=1 required="5.4 GiB" gpus=1
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=memory.go:181 msg=evaluating library=cuda gpu_count=1 available="[11.3 GiB]"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.vision.block_count default=0
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.key_length default=128
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.value_length default=128
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:611 msg="default cache size estimate" "attention MiB"=512 "attention bytes"=536870912 "recurrent MiB"=0 "recurrent bytes"=0
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=server.go:544 msg=offload library=cuda layers.requested=-1 layers.model=33 layers.offload=33 layers.split=[33] memory.available="[11.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.4 GiB" memory.required.partial="5.4 GiB" memory.required.kv="512.0 MiB" memory.required.allocations="[5.4 GiB]" memory.weights.total="4.1 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="296.0 MiB" memory.graph.partial="677.5 MiB"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=runner.go:799 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:false KvSize:4096 KvCacheType: NumThreads:8 GPULayers:33[ID:GPU-00974eaa-b009-056b-5f0e-05794f5f125c Layers:33(0..32)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:true}"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=server.go:1251 msg="waiting for llama runner to start responding"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.040+02:00 level=INFO source=server.go:1285 msg="waiting for server to become available" status="llm server loading model"
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa (version GGUF V3 (latest))
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   0:                       general.architecture str              = llama
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   1:                               general.name str              = Meta-Llama-3-8B-Instruct
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   2:                          llama.block_count u32              = 32
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   3:                       llama.context_length u32              = 8192
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 500000.000000
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  10:                          general.file_type u32              = 2
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  11:                           llama.vocab_size u32              = 128256
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = gpt2
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = llama-bpe
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  16:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  17:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 128000
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 128009
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  20:                    tokenizer.chat_template str              = {% set loop_messages = messages %}{% ...
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv  21:               general.quantization_version u32              = 2
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type  f32:   65 tensors
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type q4_0:  225 tensors
Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type q6_K:    1 tensors
Okt 12 10:43:12 airblast ollama[83240]: print_info: file format = GGUF V3 (latest)
Okt 12 10:43:12 airblast ollama[83240]: print_info: file type   = Q4_0
Okt 12 10:43:12 airblast ollama[83240]: print_info: file size   = 4.33 GiB (4.64 BPW)
Okt 12 10:43:12 airblast ollama[83240]: init_tokenizer: initializing tokenizer for type 2
Okt 12 10:43:12 airblast ollama[83240]: load: control token: 128255 '<|reserved_special_token_250|>' is not marked as EOG
...
Okt 12 10:43:12 airblast ollama[83240]: load: control token: 128123 '<|reserved_special_token_118|>' is not marked as EOG
Okt 12 10:43:12 airblast ollama[83240]: load: printing all EOG tokens:
Okt 12 10:43:12 airblast ollama[83240]: load:   - 128001 ('<|end_of_text|>')
Okt 12 10:43:12 airblast ollama[83240]: load:   - 128009 ('<|eot_id|>')
Okt 12 10:43:12 airblast ollama[83240]: load: special tokens cache size = 256
Okt 12 10:43:12 airblast ollama[83240]: load: token to piece cache size = 0.8000 MB
Okt 12 10:43:12 airblast ollama[83240]: print_info: arch             = llama
Okt 12 10:43:12 airblast ollama[83240]: print_info: vocab_only       = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ctx_train      = 8192
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd           = 4096
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_layer          = 32
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_head           = 32
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_head_kv        = 8
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_rot            = 128
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_swa            = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: is_swa_any       = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_head_k    = 128
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_head_v    = 128
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_gqa            = 4
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_k_gqa     = 1024
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_v_gqa     = 1024
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_norm_eps       = 0.0e+00
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_norm_rms_eps   = 1.0e-05
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_clamp_kqv      = 0.0e+00
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_max_alibi_bias = 0.0e+00
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_logit_scale    = 0.0e+00
Okt 12 10:43:12 airblast ollama[83240]: print_info: f_attn_scale     = 0.0e+00
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ff             = 14336
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_expert         = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_expert_used    = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: causal attn      = 1
Okt 12 10:43:12 airblast ollama[83240]: print_info: pooling type     = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: rope type        = 0
Okt 12 10:43:12 airblast ollama[83240]: print_info: rope scaling     = linear
Okt 12 10:43:12 airblast ollama[83240]: print_info: freq_base_train  = 500000.0
Okt 12 10:43:12 airblast ollama[83240]: print_info: freq_scale_train = 1
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ctx_orig_yarn  = 8192
Okt 12 10:43:12 airblast ollama[83240]: print_info: rope_finetuned   = unknown
Okt 12 10:43:12 airblast ollama[83240]: print_info: model type       = 8B
Okt 12 10:43:12 airblast ollama[83240]: print_info: model params     = 8.03 B
Okt 12 10:43:12 airblast ollama[83240]: print_info: general.name     = Meta-Llama-3-8B-Instruct
Okt 12 10:43:12 airblast ollama[83240]: print_info: vocab type       = BPE
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_vocab          = 128256
Okt 12 10:43:12 airblast ollama[83240]: print_info: n_merges         = 280147
Okt 12 10:43:12 airblast ollama[83240]: print_info: BOS token        = 128000 '<|begin_of_text|>'
Okt 12 10:43:12 airblast ollama[83240]: print_info: EOS token        = 128009 '<|eot_id|>'
Okt 12 10:43:12 airblast ollama[83240]: print_info: EOT token        = 128009 '<|eot_id|>'
Okt 12 10:43:12 airblast ollama[83240]: print_info: LF token         = 198 'Ċ'
Okt 12 10:43:12 airblast ollama[83240]: print_info: EOG token        = 128001 '<|end_of_text|>'
Okt 12 10:43:12 airblast ollama[83240]: print_info: EOG token        = 128009 '<|eot_id|>'
Okt 12 10:43:12 airblast ollama[83240]: print_info: max token length = 256
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: loading model tensors, this can take a while... (mmap = true)
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   0 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   1 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   2 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   3 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   4 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   5 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   6 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   7 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   8 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer   9 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  10 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  11 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  12 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  13 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  14 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  15 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  16 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  17 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  18 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  19 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  20 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  21 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  22 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  23 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  24 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  25 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  26 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  27 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  28 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  29 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  30 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  31 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer  32 assigned to device CPU, is_swa = 0
Okt 12 10:43:12 airblast ollama[83240]: load_tensors:   CPU_Mapped model buffer size =  4437.80 MiB
Okt 12 10:43:12 airblast ollama[83240]: llama_context: constructing llama_context
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_seq_max     = 1
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx         = 4096
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx_per_seq = 4096
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_batch       = 512
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ubatch      = 512
Okt 12 10:43:12 airblast ollama[83240]: llama_context: causal_attn   = 1
Okt 12 10:43:12 airblast ollama[83240]: llama_context: flash_attn    = 0
Okt 12 10:43:12 airblast ollama[83240]: llama_context: kv_unified    = false
Okt 12 10:43:12 airblast ollama[83240]: llama_context: freq_base     = 500000.0
Okt 12 10:43:12 airblast ollama[83240]: llama_context: freq_scale    = 1
Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (8192) -- the full capacity of the model will not be utilized
Okt 12 10:43:12 airblast ollama[83240]: set_abort_callback: call
Okt 12 10:43:12 airblast ollama[83240]: llama_context:        CPU  output buffer size =     0.50 MiB
Okt 12 10:43:12 airblast ollama[83240]: create_memory: n_ctx = 4096 (padded)
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   0: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   1: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   2: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   3: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   4: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   5: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   6: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   7: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   8: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer   9: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  10: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  11: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  12: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  13: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  14: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  15: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  16: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  17: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  18: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  19: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  20: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  21: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  22: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  23: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  24: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  25: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  26: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  27: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  28: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  29: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  30: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer  31: dev = CPU
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified:        CPU KV buffer size =   512.00 MiB
Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: size =  512.00 MiB (  4096 cells,  32 layers,  1/1 seqs), K (f16):  256.00 MiB, V (f16):  256.00 MiB
Okt 12 10:43:12 airblast ollama[83240]: llama_context: enumerating backends
Okt 12 10:43:12 airblast ollama[83240]: llama_context: backend_ptrs.size() = 1
Okt 12 10:43:12 airblast ollama[83240]: llama_context: max_nodes = 2328
Okt 12 10:43:12 airblast ollama[83240]: llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens =    1, n_seqs =  1, n_outputs =    1
Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.290+02:00 level=DEBUG source=server.go:1295 msg="model load progress 1.00"
Okt 12 10:43:12 airblast ollama[83240]: llama_context:        CPU compute buffer size =   300.01 MiB
Okt 12 10:43:12 airblast ollama[83240]: llama_context: graph nodes  = 1126
Okt 12 10:43:12 airblast ollama[83240]: llama_context: graph splits = 1
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.541+02:00 level=INFO source=server.go:1289 msg="llama runner started in 0.60 seconds"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.541+02:00 level=INFO source=sched.go:470 msg="loaded runners" count=1
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=INFO source=server.go:1251 msg="waiting for llama runner to start responding"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=INFO source=server.go:1289 msg="llama runner started in 0.60 seconds"
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=sched.go:482 msg="finished setting up" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=server.go:1388 msg="completion request" images=0 prompt=139 format=""
Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=17 used=0 remaining=17
Okt 12 10:43:15 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:15 | 200 |       21.47µs |       127.0.0.1 | HEAD     "/"
Okt 12 10:43:15 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:15 | 200 |       75.93µs |       127.0.0.1 | GET      "/api/ps"
Okt 12 10:43:42 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:42 | 200 | 31.162649767s |       127.0.0.1 | POST     "/api/generate"
Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:490 msg="context for request finished"
Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:286 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096 duration=5m0s
Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:304 msg="after processing request finished event" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096 refCount=0
Okt 12 10:43:54 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:54 | 200 |      39.881µs |       127.0.0.1 | HEAD     "/"
Okt 12 10:43:54 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:54 | 200 |      29.375µs |       127.0.0.1 | GET      "/api/ps"

OS

Linux

GPU

Nvidia

CPU

Intel

Ollama version

0.12.3

Originally created by @thomek on GitHub (Oct 12, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/12586 ### What is the issue? I'm running ```bash ollama run llama3:8b "Explain machine learning in simple terms" ``` `ollama ps` shows 100% GPU but the GPU is actually not utilized according to `nvidia-smi`. The log indicates that Ollama recognizes the GPU. But it does not load a GPU backend: ``` Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650 Okt 12 10:43:11 airblast ollama[83240]: calling cuInit Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8 Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0 Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount Okt 12 10:43:11 airblast ollama[83240]: device count 1 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=INFO source=runner.go:864 msg="starting go runner" Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/lib/ollama Okt 12 10:43:11 airblast ollama[83240]: operator() double registration of ggml_uncaught_exception Okt 12 10:43:11 airblast ollama[83240]: load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc) Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=runner.go:900 msg="Server listening on 127.0.0.1:40323" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB" Okt 12 10:43:12 airblast ollama[83240]: releasing cuda driver library ``` I'm using OpenSUSE Tumbleweed version 20251007. The Ollama version is 0.12.3 (according to `zypper`, `ollama --version` says 0.0.0). I scanned the lasted issues reported on GitHub but was not able to solve the issue myself. Thank you very much for your help if you should find the time to have a look at my problem! ### Relevant log output ```shell ollama ps NAME ID SIZE PROCESSOR CONTEXT UNTIL llama3:8b 365c0bd3c000 5.8 GB 100% GPU 4096 4 minutes from now nvidia-smi Sun Oct 12 10:43:20 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.95.05 Driver Version: 580.95.05 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | 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 NVIDIA GeForce RTX 4080 ... On | 00000000:01:00.0 On | N/A | | N/A 45C P8 3W / 175W | 137MiB / 12282MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 2352 G /usr/bin/Xorg.bin 58MiB | | 0 N/A N/A 2630 G /usr/bin/kwin_wayland 3MiB | +-----------------------------------------------------------------------------------------+ journalctl -u ollama --since '2025-10-12 10:43:00' --no-pager Okt 12 10:43:02 airblast systemd[1]: Stopping Ollama Service... Okt 12 10:43:02 airblast systemd[1]: ollama.service: Deactivated successfully. Okt 12 10:43:02 airblast systemd[1]: Stopped Ollama Service. Okt 12 10:43:02 airblast systemd[1]: ollama.service: Consumed 5min 10.842s CPU time. Okt 12 10:43:02 airblast systemd[1]: Started Ollama Service. Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.499+02:00 level=INFO source=routes.go:1475 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:4096 OLLAMA_DEBUG:DEBUG OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE:f16 OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/var/lib/ollama/.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_REMOTES:[ollama.com] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.500+02:00 level=INFO source=images.go:518 msg="total blobs: 33" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.501+02:00 level=INFO source=images.go:525 msg="total unused blobs removed: 0" Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] [WARNING] Creating an Engine instance with the Logger and Recovery middleware already attached. Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] [WARNING] Running in "debug" mode. Switch to "release" mode in production. Okt 12 10:43:02 airblast ollama[83240]: - using env: export GIN_MODE=release Okt 12 10:43:02 airblast ollama[83240]: - using code: gin.SetMode(gin.ReleaseMode) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD / --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func1 (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET / --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func2 (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD /api/version --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func3 (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET /api/version --> github.com/ollama/ollama/server.(*Server).GenerateRoutes.func4 (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/pull --> github.com/ollama/ollama/server.(*Server).PullHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/push --> github.com/ollama/ollama/server.(*Server).PushHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD /api/tags --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET /api/tags --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/show --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] DELETE /api/delete --> github.com/ollama/ollama/server.(*Server).DeleteHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/me --> github.com/ollama/ollama/server.(*Server).WhoamiHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/signout --> github.com/ollama/ollama/server.(*Server).SignoutHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] DELETE /api/user/keys/:encodedKey --> github.com/ollama/ollama/server.(*Server).SignoutHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/create --> github.com/ollama/ollama/server.(*Server).CreateHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/blobs/:digest --> github.com/ollama/ollama/server.(*Server).CreateBlobHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] HEAD /api/blobs/:digest --> github.com/ollama/ollama/server.(*Server).HeadBlobHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/copy --> github.com/ollama/ollama/server.(*Server).CopyHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET /api/ps --> github.com/ollama/ollama/server.(*Server).PsHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/generate --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/chat --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/embed --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /api/embeddings --> github.com/ollama/ollama/server.(*Server).EmbeddingsHandler-fm (5 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /v1/chat/completions --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /v1/completions --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] POST /v1/embeddings --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET /v1/models --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (6 handlers) Okt 12 10:43:02 airblast ollama[83240]: [GIN-debug] GET /v1/models/:model --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (6 handlers) Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=INFO source=routes.go:1528 msg="Listening on 127.0.0.1:11434 (version 0.0.0)" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=DEBUG source=sched.go:121 msg="starting llm scheduler" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.502+02:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:98 msg="searching for GPU discovery libraries for NVIDIA" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:520 msg="Searching for GPU library" name=libcuda.so* Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.503+02:00 level=DEBUG source=gpu.go:544 msg="gpu library search" globs="[/usr/lib/ollama/libcuda.so* /libcuda.so* /usr/local/cuda*/targets/*/lib/libcuda.so* /usr/lib/*-linux-gnu/nvidia/current/libcuda.so* /usr/lib/*-linux-gnu/libcuda.so* /usr/lib/wsl/lib/libcuda.so* /usr/lib/wsl/drivers/*/libcuda.so* /opt/cuda/lib*/libcuda.so* /usr/local/cuda/lib*/libcuda.so* /usr/lib*/libcuda.so* /usr/local/lib*/libcuda.so*]" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.505+02:00 level=DEBUG source=gpu.go:577 msg="discovered GPU libraries" paths=[/usr/lib64/libcuda.so.580.95.05] Okt 12 10:43:02 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460 Okt 12 10:43:02 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650 Okt 12 10:43:02 airblast ollama[83240]: calling cuInit Okt 12 10:43:02 airblast ollama[83240]: calling cuDriverGetVersion Okt 12 10:43:02 airblast ollama[83240]: raw version 0x32c8 Okt 12 10:43:02 airblast ollama[83240]: CUDA driver version: 13.0 Okt 12 10:43:02 airblast ollama[83240]: calling cuDeviceGetCount Okt 12 10:43:02 airblast ollama[83240]: device count 1 Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.616+02:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=/usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] CUDA totalMem 11874mb Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] CUDA freeMem 11546mb Okt 12 10:43:02 airblast ollama[83240]: [GPU-00974eaa-b009-056b-5f0e-05794f5f125c] Compute Capability 8.9 Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=DEBUG source=amd_linux.go:423 msg="amdgpu driver not detected /sys/module/amdgpu" Okt 12 10:43:02 airblast ollama[83240]: releasing cuda driver library Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=INFO source=types.go:131 msg="inference compute" id=GPU-00974eaa-b009-056b-5f0e-05794f5f125c library=cuda variant=v13 compute=8.9 driver=13.0 name="NVIDIA GeForce RTX 4080 Laptop GPU" total="11.6 GiB" available="11.3 GiB" Okt 12 10:43:02 airblast ollama[83240]: time=2025-10-12T10:43:02.719+02:00 level=INFO source=routes.go:1569 msg="entering low vram mode" "total vram"="11.6 GiB" threshold="20.0 GiB" Okt 12 10:43:11 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:11 | 200 | 24.247µs | 127.0.0.1 | HEAD "/" Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.524+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=general.alignment default=32 Okt 12 10:43:11 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:11 | 200 | 48.541925ms | 127.0.0.1 | POST "/api/show" Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.588+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.4 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.3 GiB" now.free_swap="96.0 GiB" Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650 Okt 12 10:43:11 airblast ollama[83240]: calling cuInit Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8 Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0 Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount Okt 12 10:43:11 airblast ollama[83240]: device count 1 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.690+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB" Okt 12 10:43:11 airblast ollama[83240]: releasing cuda driver library Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.690+02:00 level=DEBUG source=sched.go:188 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.698+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=general.alignment default=32 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.698+02:00 level=DEBUG source=sched.go:208 msg="loading first model" model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa (version GGUF V3 (latest)) Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 0: general.architecture str = llama Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 1: general.name str = Meta-Llama-3-8B-Instruct Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 2: llama.block_count u32 = 32 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 3: llama.context_length u32 = 8192 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 8: llama.rope.freq_base f32 = 500000.000000 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 10: general.file_type u32 = 2 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 11: llama.vocab_size u32 = 128256 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 14: tokenizer.ggml.pre str = llama-bpe Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128009 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 20: tokenizer.chat_template str = {% set loop_messages = messages %}{% ... Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - kv 21: general.quantization_version u32 = 2 Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type f32: 65 tensors Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type q4_0: 225 tensors Okt 12 10:43:11 airblast ollama[83240]: llama_model_loader: - type q6_K: 1 tensors Okt 12 10:43:11 airblast ollama[83240]: print_info: file format = GGUF V3 (latest) Okt 12 10:43:11 airblast ollama[83240]: print_info: file type = Q4_0 Okt 12 10:43:11 airblast ollama[83240]: print_info: file size = 4.33 GiB (4.64 BPW) Okt 12 10:43:11 airblast ollama[83240]: init_tokenizer: initializing tokenizer for type 2 Okt 12 10:43:11 airblast ollama[83240]: load: control token: 128255 '<|reserved_special_token_250|>' is not marked as EOG ... Okt 12 10:43:11 airblast ollama[83240]: load: control token: 128123 '<|reserved_special_token_118|>' is not marked as EOG Okt 12 10:43:11 airblast ollama[83240]: load: printing all EOG tokens: Okt 12 10:43:11 airblast ollama[83240]: load: - 128001 ('<|end_of_text|>') Okt 12 10:43:11 airblast ollama[83240]: load: - 128009 ('<|eot_id|>') Okt 12 10:43:11 airblast ollama[83240]: load: special tokens cache size = 256 Okt 12 10:43:11 airblast ollama[83240]: load: token to piece cache size = 0.8000 MB Okt 12 10:43:11 airblast ollama[83240]: print_info: arch = llama Okt 12 10:43:11 airblast ollama[83240]: print_info: vocab_only = 1 Okt 12 10:43:11 airblast ollama[83240]: print_info: model type = ?B Okt 12 10:43:11 airblast ollama[83240]: print_info: model params = 8.03 B Okt 12 10:43:11 airblast ollama[83240]: print_info: general.name = Meta-Llama-3-8B-Instruct Okt 12 10:43:11 airblast ollama[83240]: print_info: vocab type = BPE Okt 12 10:43:11 airblast ollama[83240]: print_info: n_vocab = 128256 Okt 12 10:43:11 airblast ollama[83240]: print_info: n_merges = 280147 Okt 12 10:43:11 airblast ollama[83240]: print_info: BOS token = 128000 '<|begin_of_text|>' Okt 12 10:43:11 airblast ollama[83240]: print_info: EOS token = 128009 '<|eot_id|>' Okt 12 10:43:11 airblast ollama[83240]: print_info: EOT token = 128009 '<|eot_id|>' Okt 12 10:43:11 airblast ollama[83240]: print_info: LF token = 198 'Ċ' Okt 12 10:43:11 airblast ollama[83240]: print_info: EOG token = 128001 '<|end_of_text|>' Okt 12 10:43:11 airblast ollama[83240]: print_info: EOG token = 128009 '<|eot_id|>' Okt 12 10:43:11 airblast ollama[83240]: print_info: max token length = 256 Okt 12 10:43:11 airblast ollama[83240]: llama_model_load: vocab only - skipping tensors Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.855+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.3 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.2 GiB" now.free_swap="96.0 GiB" Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650 Okt 12 10:43:11 airblast ollama[83240]: calling cuInit Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8 Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0 Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount Okt 12 10:43:11 airblast ollama[83240]: device count 1 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB" Okt 12 10:43:11 airblast ollama[83240]: releasing cuda driver library Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=INFO source=server.go:399 msg="starting runner" cmd="/usr/bin/ollama runner --model /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa --port 40323" Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.945+02:00 level=DEBUG source=server.go:400 msg=subprocess PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin OLLAMA_DEBUG=1 OLLAMA_LOG_LEVEL=debug OLLAMA_HOST=http://127.0.0.1:11434 OLLAMA_KV_CACHE_TYPE=f16 OLLAMA_KEEP_ALIVE="" OLLAMA_NUM_PARALLEL="" OLLAMA_MAX_VRAM="" OLLAMA_RUNNERS_DIR="" OLLAMA_TMPDIR="" OLLAMA_MODELS="" OLLAMA_ORIGINS="" OLLAMA_MAX_LOADED_MODELS=3 OLLAMA_LIBRARY_PATH=/usr/lib/ollama LD_LIBRARY_PATH=/usr/lib/ollama:/usr/lib/ollama Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.946+02:00 level=DEBUG source=gpu.go:410 msg="updating system memory data" before.total="62.5 GiB" before.free="57.2 GiB" before.free_swap="96.0 GiB" now.total="62.5 GiB" now.free="57.2 GiB" now.free_swap="96.0 GiB" Okt 12 10:43:11 airblast ollama[83240]: initializing /usr/lib64/libcuda.so.580.95.05 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuInit - 0x7f9a3e505d00 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDriverGetVersion - 0x7f9a3e505dc0 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetCount - 0x7f9a3e505f40 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGet - 0x7f9a3e505e80 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetAttribute - 0x7f9a3e528f20 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetUuid - 0x7f9a3e57bd10 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuDeviceGetName - 0x7f9a3e506000 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxCreate_v3 - 0x7f9a3e579750 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuMemGetInfo_v2 - 0x7f9a3e52d460 Okt 12 10:43:11 airblast ollama[83240]: dlsym: cuCtxDestroy - 0x7f9a3e57b650 Okt 12 10:43:11 airblast ollama[83240]: calling cuInit Okt 12 10:43:11 airblast ollama[83240]: calling cuDriverGetVersion Okt 12 10:43:11 airblast ollama[83240]: raw version 0x32c8 Okt 12 10:43:11 airblast ollama[83240]: CUDA driver version: 13.0 Okt 12 10:43:11 airblast ollama[83240]: calling cuDeviceGetCount Okt 12 10:43:11 airblast ollama[83240]: device count 1 Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=INFO source=runner.go:864 msg="starting go runner" Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.954+02:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/lib/ollama Okt 12 10:43:11 airblast ollama[83240]: operator() double registration of ggml_uncaught_exception Okt 12 10:43:11 airblast ollama[83240]: load_backend: loaded CPU backend from /usr/lib/ollama/libggml-cpu-alderlake.so Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc) Okt 12 10:43:11 airblast ollama[83240]: time=2025-10-12T10:43:11.959+02:00 level=INFO source=runner.go:900 msg="Server listening on 127.0.0.1:40323" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=gpu.go:460 msg="updating cuda memory data" gpu=GPU-00974eaa-b009-056b-5f0e-05794f5f125c name="NVIDIA GeForce RTX 4080 Laptop GPU" overhead="0 B" before.total="11.6 GiB" before.free="11.3 GiB" now.total="11.6 GiB" now.free="11.3 GiB" now.used="327.9 MiB" Okt 12 10:43:12 airblast ollama[83240]: releasing cuda driver library Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=INFO source=server.go:504 msg="system memory" total="62.5 GiB" free="57.2 GiB" free_swap="96.0 GiB" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=memory.go:181 msg=evaluating library=cuda gpu_count=1 available="[11.3 GiB]" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.vision.block_count default=0 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.038+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.key_length default=128 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.value_length default=128 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:611 msg="default cache size estimate" "attention MiB"=512 "attention bytes"=536870912 "recurrent MiB"=0 "recurrent bytes"=0 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=memory.go:36 msg="new model will fit in available VRAM across minimum required GPUs, loading" model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa library=cuda parallel=1 required="5.4 GiB" gpus=1 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=memory.go:181 msg=evaluating library=cuda gpu_count=1 available="[11.3 GiB]" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.vision.block_count default=0 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.key_length default=128 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:276 msg="key with type not found" key=llama.attention.value_length default=128 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=DEBUG source=ggml.go:611 msg="default cache size estimate" "attention MiB"=512 "attention bytes"=536870912 "recurrent MiB"=0 "recurrent bytes"=0 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=server.go:544 msg=offload library=cuda layers.requested=-1 layers.model=33 layers.offload=33 layers.split=[33] memory.available="[11.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.4 GiB" memory.required.partial="5.4 GiB" memory.required.kv="512.0 MiB" memory.required.allocations="[5.4 GiB]" memory.weights.total="4.1 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="296.0 MiB" memory.graph.partial="677.5 MiB" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=runner.go:799 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:false KvSize:4096 KvCacheType: NumThreads:8 GPULayers:33[ID:GPU-00974eaa-b009-056b-5f0e-05794f5f125c Layers:33(0..32)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:true}" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.039+02:00 level=INFO source=server.go:1251 msg="waiting for llama runner to start responding" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.040+02:00 level=INFO source=server.go:1285 msg="waiting for server to become available" status="llm server loading model" Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa (version GGUF V3 (latest)) Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 0: general.architecture str = llama Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 1: general.name str = Meta-Llama-3-8B-Instruct Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 2: llama.block_count u32 = 32 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 3: llama.context_length u32 = 8192 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 8: llama.rope.freq_base f32 = 500000.000000 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 10: general.file_type u32 = 2 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 11: llama.vocab_size u32 = 128256 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 14: tokenizer.ggml.pre str = llama-bpe Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128009 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 20: tokenizer.chat_template str = {% set loop_messages = messages %}{% ... Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - kv 21: general.quantization_version u32 = 2 Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type f32: 65 tensors Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type q4_0: 225 tensors Okt 12 10:43:12 airblast ollama[83240]: llama_model_loader: - type q6_K: 1 tensors Okt 12 10:43:12 airblast ollama[83240]: print_info: file format = GGUF V3 (latest) Okt 12 10:43:12 airblast ollama[83240]: print_info: file type = Q4_0 Okt 12 10:43:12 airblast ollama[83240]: print_info: file size = 4.33 GiB (4.64 BPW) Okt 12 10:43:12 airblast ollama[83240]: init_tokenizer: initializing tokenizer for type 2 Okt 12 10:43:12 airblast ollama[83240]: load: control token: 128255 '<|reserved_special_token_250|>' is not marked as EOG ... Okt 12 10:43:12 airblast ollama[83240]: load: control token: 128123 '<|reserved_special_token_118|>' is not marked as EOG Okt 12 10:43:12 airblast ollama[83240]: load: printing all EOG tokens: Okt 12 10:43:12 airblast ollama[83240]: load: - 128001 ('<|end_of_text|>') Okt 12 10:43:12 airblast ollama[83240]: load: - 128009 ('<|eot_id|>') Okt 12 10:43:12 airblast ollama[83240]: load: special tokens cache size = 256 Okt 12 10:43:12 airblast ollama[83240]: load: token to piece cache size = 0.8000 MB Okt 12 10:43:12 airblast ollama[83240]: print_info: arch = llama Okt 12 10:43:12 airblast ollama[83240]: print_info: vocab_only = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ctx_train = 8192 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd = 4096 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_layer = 32 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_head = 32 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_head_kv = 8 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_rot = 128 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: is_swa_any = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_head_k = 128 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_head_v = 128 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_gqa = 4 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_k_gqa = 1024 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_embd_v_gqa = 1024 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_norm_eps = 0.0e+00 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_norm_rms_eps = 1.0e-05 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_clamp_kqv = 0.0e+00 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_max_alibi_bias = 0.0e+00 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_logit_scale = 0.0e+00 Okt 12 10:43:12 airblast ollama[83240]: print_info: f_attn_scale = 0.0e+00 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ff = 14336 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_expert = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_expert_used = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: causal attn = 1 Okt 12 10:43:12 airblast ollama[83240]: print_info: pooling type = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: rope type = 0 Okt 12 10:43:12 airblast ollama[83240]: print_info: rope scaling = linear Okt 12 10:43:12 airblast ollama[83240]: print_info: freq_base_train = 500000.0 Okt 12 10:43:12 airblast ollama[83240]: print_info: freq_scale_train = 1 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_ctx_orig_yarn = 8192 Okt 12 10:43:12 airblast ollama[83240]: print_info: rope_finetuned = unknown Okt 12 10:43:12 airblast ollama[83240]: print_info: model type = 8B Okt 12 10:43:12 airblast ollama[83240]: print_info: model params = 8.03 B Okt 12 10:43:12 airblast ollama[83240]: print_info: general.name = Meta-Llama-3-8B-Instruct Okt 12 10:43:12 airblast ollama[83240]: print_info: vocab type = BPE Okt 12 10:43:12 airblast ollama[83240]: print_info: n_vocab = 128256 Okt 12 10:43:12 airblast ollama[83240]: print_info: n_merges = 280147 Okt 12 10:43:12 airblast ollama[83240]: print_info: BOS token = 128000 '<|begin_of_text|>' Okt 12 10:43:12 airblast ollama[83240]: print_info: EOS token = 128009 '<|eot_id|>' Okt 12 10:43:12 airblast ollama[83240]: print_info: EOT token = 128009 '<|eot_id|>' Okt 12 10:43:12 airblast ollama[83240]: print_info: LF token = 198 'Ċ' Okt 12 10:43:12 airblast ollama[83240]: print_info: EOG token = 128001 '<|end_of_text|>' Okt 12 10:43:12 airblast ollama[83240]: print_info: EOG token = 128009 '<|eot_id|>' Okt 12 10:43:12 airblast ollama[83240]: print_info: max token length = 256 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: loading model tensors, this can take a while... (mmap = true) Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 0 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 1 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 2 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 3 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 4 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 5 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 6 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 7 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 8 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 9 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 10 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 11 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 12 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 13 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 14 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 15 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 16 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 17 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 18 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 19 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 20 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 21 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 22 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 23 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 24 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 25 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 26 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 27 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 28 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 29 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 30 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 31 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: layer 32 assigned to device CPU, is_swa = 0 Okt 12 10:43:12 airblast ollama[83240]: load_tensors: CPU_Mapped model buffer size = 4437.80 MiB Okt 12 10:43:12 airblast ollama[83240]: llama_context: constructing llama_context Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_seq_max = 1 Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx = 4096 Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx_per_seq = 4096 Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_batch = 512 Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ubatch = 512 Okt 12 10:43:12 airblast ollama[83240]: llama_context: causal_attn = 1 Okt 12 10:43:12 airblast ollama[83240]: llama_context: flash_attn = 0 Okt 12 10:43:12 airblast ollama[83240]: llama_context: kv_unified = false Okt 12 10:43:12 airblast ollama[83240]: llama_context: freq_base = 500000.0 Okt 12 10:43:12 airblast ollama[83240]: llama_context: freq_scale = 1 Okt 12 10:43:12 airblast ollama[83240]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (8192) -- the full capacity of the model will not be utilized Okt 12 10:43:12 airblast ollama[83240]: set_abort_callback: call Okt 12 10:43:12 airblast ollama[83240]: llama_context: CPU output buffer size = 0.50 MiB Okt 12 10:43:12 airblast ollama[83240]: create_memory: n_ctx = 4096 (padded) Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 0: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 1: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 2: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 3: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 4: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 5: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 6: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 7: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 8: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 9: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 10: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 11: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 12: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 13: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 14: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 15: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 16: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 17: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 18: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 19: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 20: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 21: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 22: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 23: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 24: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 25: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 26: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 27: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 28: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 29: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 30: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: layer 31: dev = CPU Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: CPU KV buffer size = 512.00 MiB Okt 12 10:43:12 airblast ollama[83240]: llama_kv_cache_unified: size = 512.00 MiB ( 4096 cells, 32 layers, 1/1 seqs), K (f16): 256.00 MiB, V (f16): 256.00 MiB Okt 12 10:43:12 airblast ollama[83240]: llama_context: enumerating backends Okt 12 10:43:12 airblast ollama[83240]: llama_context: backend_ptrs.size() = 1 Okt 12 10:43:12 airblast ollama[83240]: llama_context: max_nodes = 2328 Okt 12 10:43:12 airblast ollama[83240]: llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0 Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens = 512, n_seqs = 1, n_outputs = 512 Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens = 1, n_seqs = 1, n_outputs = 1 Okt 12 10:43:12 airblast ollama[83240]: graph_reserve: reserving a graph for ubatch with n_tokens = 512, n_seqs = 1, n_outputs = 512 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.290+02:00 level=DEBUG source=server.go:1295 msg="model load progress 1.00" Okt 12 10:43:12 airblast ollama[83240]: llama_context: CPU compute buffer size = 300.01 MiB Okt 12 10:43:12 airblast ollama[83240]: llama_context: graph nodes = 1126 Okt 12 10:43:12 airblast ollama[83240]: llama_context: graph splits = 1 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.541+02:00 level=INFO source=server.go:1289 msg="llama runner started in 0.60 seconds" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.541+02:00 level=INFO source=sched.go:470 msg="loaded runners" count=1 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=INFO source=server.go:1251 msg="waiting for llama runner to start responding" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=INFO source=server.go:1289 msg="llama runner started in 0.60 seconds" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=sched.go:482 msg="finished setting up" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096 Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=server.go:1388 msg="completion request" images=0 prompt=139 format="" Okt 12 10:43:12 airblast ollama[83240]: time=2025-10-12T10:43:12.542+02:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=17 used=0 remaining=17 Okt 12 10:43:15 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:15 | 200 | 21.47µs | 127.0.0.1 | HEAD "/" Okt 12 10:43:15 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:15 | 200 | 75.93µs | 127.0.0.1 | GET "/api/ps" Okt 12 10:43:42 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:42 | 200 | 31.162649767s | 127.0.0.1 | POST "/api/generate" Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:490 msg="context for request finished" Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:286 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096 duration=5m0s Okt 12 10:43:42 airblast ollama[83240]: time=2025-10-12T10:43:42.688+02:00 level=DEBUG source=sched.go:304 msg="after processing request finished event" runner.name=registry.ollama.ai/library/llama3:8b runner.inference=cuda runner.devices=1 runner.size="5.4 GiB" runner.vram="5.4 GiB" runner.parallel=1 runner.pid=83281 runner.model=/var/lib/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa runner.num_ctx=4096 refCount=0 Okt 12 10:43:54 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:54 | 200 | 39.881µs | 127.0.0.1 | HEAD "/" Okt 12 10:43:54 airblast ollama[83240]: [GIN] 2025/10/12 - 10:43:54 | 200 | 29.375µs | 127.0.0.1 | GET "/api/ps" ``` ### OS Linux ### GPU Nvidia ### CPU Intel ### Ollama version 0.12.3

GiteaMirror added the bug label 2026-04-12 20:57:08 -05:00

GiteaMirror closed this issue 2026-04-12 20:57:10 -05:00

GiteaMirror commented 2026-04-12 20:57:11 -05:00

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@thomek commented on GitHub (Oct 12, 2025):

ls -l /usr/lib/ollama shows

drwxr-xr-x. 1 root root    340 12. Okt 11:08 ./
dr-xr-xr-x. 1 root root   1204 12. Okt 11:08 ../
-rwxr-xr-x. 1 root root 489816  4. Okt 20:37 libggml-base.so*
-rwxr-xr-x. 1 root root 584216  4. Okt 20:37 libggml-cpu-alderlake.so*
-rwxr-xr-x. 1 root root 584216  4. Okt 20:37 libggml-cpu-haswell.so*
-rwxr-xr-x. 1 root root 682520  4. Okt 20:37 libggml-cpu-icelake.so*
-rwxr-xr-x. 1 root root 518680  4. Okt 20:37 libggml-cpu-sandybridge.so*
-rwxr-xr-x. 1 root root 682520  4. Okt 20:37 libggml-cpu-skylakex.so*
-rwxr-xr-x. 1 root root 449040  4. Okt 20:37 libggml-cpu-sse42.so*
-rwxr-xr-x. 1 root root 440848  4. Okt 20:37 libggml-cpu-x64.so*

I searched for libggml-cuda.so - which is included in the download artifact ollama-linux-amd64.tgz for version 0.12.3 - but it is not installed on my system.

I installed libggml* via YaST. But those packages don't include libggml-cuda.so either.

Looks like a Tumbleweed related issue. Therefore this is not the right place for my question. I'm closing this issue.

<!-- gh-comment-id:3394126093 --> @thomek commented on GitHub (Oct 12, 2025): `ls -l /usr/lib/ollama` shows ``` drwxr-xr-x. 1 root root 340 12. Okt 11:08 ./ dr-xr-xr-x. 1 root root 1204 12. Okt 11:08 ../ -rwxr-xr-x. 1 root root 489816 4. Okt 20:37 libggml-base.so* -rwxr-xr-x. 1 root root 584216 4. Okt 20:37 libggml-cpu-alderlake.so* -rwxr-xr-x. 1 root root 584216 4. Okt 20:37 libggml-cpu-haswell.so* -rwxr-xr-x. 1 root root 682520 4. Okt 20:37 libggml-cpu-icelake.so* -rwxr-xr-x. 1 root root 518680 4. Okt 20:37 libggml-cpu-sandybridge.so* -rwxr-xr-x. 1 root root 682520 4. Okt 20:37 libggml-cpu-skylakex.so* -rwxr-xr-x. 1 root root 449040 4. Okt 20:37 libggml-cpu-sse42.so* -rwxr-xr-x. 1 root root 440848 4. Okt 20:37 libggml-cpu-x64.so* ``` I searched for `libggml-cuda.so` - which is included in the download artifact ollama-linux-amd64.tgz for version 0.12.3 - but it is not installed on my system. I installed libggml* via YaST. But those packages don't include libggml-cuda.so either. Looks like a Tumbleweed related issue. Therefore this is not the right place for my question. I'm closing this issue.

GiteaMirror referenced this issue 2026-04-13 00:07:12 -05:00

[PR #8352] [MERGED] Add LangChain for .NET to libraries list #12693

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Reference: github-starred/ollama#8352