What is the issue?
Today, Ollama prompted me to update when I tried to run Qwen3:14b. I ran the oneline install command (curl -fsSL https://ollama.com/install.sh | sh), and during the install, it said "Nvidia GPU installed.", even though I run an AMD card. Now, whenever I try to run a model, it won't use my gfx card.
Right before updating, I observed my GPU being utilized with radeontop. I watched the VRAM fill up, etc. Now, I can see that my Graphics card isn't being utilized at all in radeontop, but my cores all go to 100 in htop - even small models run painfully slow. I am certain that this behavior began immediately after running the install script. (And yes, I have ROCm installed.)
I tried to force the backend, which didn't seem to work:
OLLAMA_GPU_BACKEND=rocm ollama run mymodel
I can also verify that my GPU is visible to ROCm, and I have no NVIDIA card in my machine.
Here's what I get when I run journalctl -u ollama --no-pager --follow --pager-end
... msg="looking for compatible GPUs"
... msg="no nvidia devices detected by library /usr/lib/x86_64-linux-gnu/libcuda.so.570.133.07"
... msg="amdgpu is supported" gpu=0 gpu_type=gfx1102
... msg="inference compute" id=0 library=rocm variant="" compute=gfx1102 driver=6.12 name=1002:7480 total="16.0 GiB" available="15.8 GiB"
... msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e gpu=0 parallel=2 available=16404119552 required="11.2 GiB"
... msg="system memory" total="78.5 GiB" free="75.3 GiB" free_swap="8.0 GiB"
... msg=offload library=rocm layers.requested=-1 layers.model=41 layers.offload=41 layers.split="" memory.available="[15.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="11.2 GiB" memory.required.partial="11.2 GiB" memory.required.kv="1.2 GiB" memory.required.allocations="[11.2 GiB]" memory.weights.total="8.2 GiB" memory.weights.repeating="7.6 GiB" memory.weights.nonrepeating="608.6 MiB" memory.graph.full="1.0 GiB" memory.graph.partial="1.0 GiB"
.... llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (version GGUF V3 (latest))
So, from what I can tell, Ollama sees my GPU, identifies that there is enough VRAM to hold the model, identifies that rocm is installed, yet makes the conscious choice to try and run the model on my CPU instead.... Unless there something obvious I'm missing, I am pretty sure this is a bug?
Neofetch:
OS: Ubuntu 24.04.2 LTS x86_64
Host: B460MDS3HV2 -CF
Kernel: 6.11.0-26-generic
Uptime: 5 mins
Packages: 3559 (dpkg), 5 (flatpak), 16 (snap)
Shell: bash 5.2.21
Resolution: 2560x1440
DE: GNOME 46.0
WM: Mutter
WM Theme: Adwaita
Theme: Yaru-blue-dark [GTK2/3]
Icons: Yaru-blue [GTK2/3]
Terminal: gnome-terminal
CPU: Intel i7-10700K (16) @ 5.100GHz
GPU: AMD ATI Radeon RX 7600/7600 XT/7600M XT/7600S/7700S / PRO W7600
Memory: 4550MiB / 80346MiB
ollama --version:
ollama version is 0.7.1
Relevant log output
May 27 21:06:38 tank systemd[1]: Started ollama.service - Ollama Service.
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.668-05:00 level=INFO source=routes.go:1205 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:4096 OLLAMA_DEBUG:INFO OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/usr/share/ollama/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.677-05:00 level=INFO source=images.go:463 msg="total blobs: 37"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.677-05:00 level=INFO source=images.go:470 msg="total unused blobs removed: 0"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.677-05:00 level=INFO source=routes.go:1258 msg="Listening on 127.0.0.1:11434 (version 0.7.1)"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.678-05:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.701-05:00 level=INFO source=gpu.go:602 msg="no nvidia devices detected by library /usr/lib/x86_64-linux-gnu/libcuda.so.570.133.07"
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.727-05:00 level=INFO source=amd_linux.go:386 msg="amdgpu is supported" gpu=0 gpu_type=gfx1102
May 27 21:06:38 tank ollama[3099]: time=2025-05-27T21:06:38.730-05:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=rocm variant="" compute=gfx1102 driver=6.12 name=1002:7480 total="16.0 GiB" available="15.8 GiB"
May 27 21:07:12 tank ollama[3099]: [GIN] 2025/05/27 - 21:07:12 | 204 | 554.384µs | 127.0.0.1 | OPTIONS "/api/tags"
May 27 21:07:12 tank ollama[3099]: [GIN] 2025/05/27 - 21:07:12 | 200 | 2.145944ms | 127.0.0.1 | GET "/api/tags"
May 27 21:07:26 tank ollama[3099]: [GIN] 2025/05/27 - 21:07:26 | 204 | 15.502µs | 127.0.0.1 | OPTIONS "/api/chat"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.392-05:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e gpu=0 parallel=2 available=16404119552 required="11.2 GiB"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.392-05:00 level=INFO source=server.go:135 msg="system memory" total="78.5 GiB" free="75.3 GiB" free_swap="8.0 GiB"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.393-05:00 level=INFO source=server.go:168 msg=offload library=rocm layers.requested=-1 layers.model=41 layers.offload=41 layers.split="" memory.available="[15.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="11.2 GiB" memory.required.partial="11.2 GiB" memory.required.kv="1.2 GiB" memory.required.allocations="[11.2 GiB]" memory.weights.total="8.2 GiB" memory.weights.repeating="7.6 GiB" memory.weights.nonrepeating="608.6 MiB" memory.graph.full="1.0 GiB" memory.graph.partial="1.0 GiB"
May 27 21:07:26 tank ollama[3099]: llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (version GGUF V3 (latest))
May 27 21:07:26 tank ollama[3099]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 0: general.architecture str = qwen3
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 1: general.type str = model
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 2: general.name str = Qwen3 14B
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 3: general.basename str = Qwen3
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 4: general.size_label str = 14B
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 5: qwen3.block_count u32 = 40
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 25: general.quantization_version u32 = 2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 26: general.file_type u32 = 15
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type f32: 161 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type f16: 40 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type q4_K: 221 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type q6_K: 21 tensors
May 27 21:07:26 tank ollama[3099]: print_info: file format = GGUF V3 (latest)
May 27 21:07:26 tank ollama[3099]: print_info: file type = Q4_K - Medium
May 27 21:07:26 tank ollama[3099]: print_info: file size = 8.63 GiB (5.02 BPW)
May 27 21:07:26 tank ollama[3099]: load: special tokens cache size = 26
May 27 21:07:26 tank ollama[3099]: load: token to piece cache size = 0.9311 MB
May 27 21:07:26 tank ollama[3099]: print_info: arch = qwen3
May 27 21:07:26 tank ollama[3099]: print_info: vocab_only = 1
May 27 21:07:26 tank ollama[3099]: print_info: model type = ?B
May 27 21:07:26 tank ollama[3099]: print_info: model params = 14.77 B
May 27 21:07:26 tank ollama[3099]: print_info: general.name = Qwen3 14B
May 27 21:07:26 tank ollama[3099]: print_info: vocab type = BPE
May 27 21:07:26 tank ollama[3099]: print_info: n_vocab = 151936
May 27 21:07:26 tank ollama[3099]: print_info: n_merges = 151387
May 27 21:07:26 tank ollama[3099]: print_info: BOS token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOS token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOT token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: PAD token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: LF token = 198 'Ċ'
May 27 21:07:26 tank ollama[3099]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM MID token = 151660 '<|fim_middle|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM REP token = 151663 '<|repo_name|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM SEP token = 151664 '<|file_sep|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151662 '<|fim_pad|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151663 '<|repo_name|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151664 '<|file_sep|>'
May 27 21:07:26 tank ollama[3099]: print_info: max token length = 256
May 27 21:07:26 tank ollama[3099]: llama_model_load: vocab only - skipping tensors
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.584-05:00 level=INFO source=server.go:431 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e --ctx-size 8192 --batch-size 512 --n-gpu-layers 41 --threads 8 --parallel 2 --port 43613"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.584-05:00 level=INFO source=sched.go:483 msg="loaded runners" count=1
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.584-05:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.585-05:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server not responding"
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.591-05:00 level=INFO source=runner.go:815 msg="starting go runner"
May 27 21:07:26 tank ollama[3099]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-haswell.so
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.601-05:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc)
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.602-05:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:43613"
May 27 21:07:26 tank ollama[3099]: llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e (version GGUF V3 (latest))
May 27 21:07:26 tank ollama[3099]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 0: general.architecture str = qwen3
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 1: general.type str = model
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 2: general.name str = Qwen3 14B
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 3: general.basename str = Qwen3
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 4: general.size_label str = 14B
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 5: qwen3.block_count u32 = 40
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 5120
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 17408
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 40
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 25: general.quantization_version u32 = 2
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - kv 26: general.file_type u32 = 15
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type f32: 161 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type f16: 40 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type q4_K: 221 tensors
May 27 21:07:26 tank ollama[3099]: llama_model_loader: - type q6_K: 21 tensors
May 27 21:07:26 tank ollama[3099]: print_info: file format = GGUF V3 (latest)
May 27 21:07:26 tank ollama[3099]: print_info: file type = Q4_K - Medium
May 27 21:07:26 tank ollama[3099]: print_info: file size = 8.63 GiB (5.02 BPW)
May 27 21:07:26 tank ollama[3099]: load: special tokens cache size = 26
May 27 21:07:26 tank ollama[3099]: load: token to piece cache size = 0.9311 MB
May 27 21:07:26 tank ollama[3099]: print_info: arch = qwen3
May 27 21:07:26 tank ollama[3099]: print_info: vocab_only = 0
May 27 21:07:26 tank ollama[3099]: print_info: n_ctx_train = 40960
May 27 21:07:26 tank ollama[3099]: print_info: n_embd = 5120
May 27 21:07:26 tank ollama[3099]: print_info: n_layer = 40
May 27 21:07:26 tank ollama[3099]: print_info: n_head = 40
May 27 21:07:26 tank ollama[3099]: print_info: n_head_kv = 8
May 27 21:07:26 tank ollama[3099]: print_info: n_rot = 128
May 27 21:07:26 tank ollama[3099]: print_info: n_swa = 0
May 27 21:07:26 tank ollama[3099]: print_info: n_swa_pattern = 1
May 27 21:07:26 tank ollama[3099]: print_info: n_embd_head_k = 128
May 27 21:07:26 tank ollama[3099]: print_info: n_embd_head_v = 128
May 27 21:07:26 tank ollama[3099]: print_info: n_gqa = 5
May 27 21:07:26 tank ollama[3099]: print_info: n_embd_k_gqa = 1024
May 27 21:07:26 tank ollama[3099]: print_info: n_embd_v_gqa = 1024
May 27 21:07:26 tank ollama[3099]: print_info: f_norm_eps = 0.0e+00
May 27 21:07:26 tank ollama[3099]: print_info: f_norm_rms_eps = 1.0e-06
May 27 21:07:26 tank ollama[3099]: print_info: f_clamp_kqv = 0.0e+00
May 27 21:07:26 tank ollama[3099]: print_info: f_max_alibi_bias = 0.0e+00
May 27 21:07:26 tank ollama[3099]: print_info: f_logit_scale = 0.0e+00
May 27 21:07:26 tank ollama[3099]: print_info: f_attn_scale = 0.0e+00
May 27 21:07:26 tank ollama[3099]: print_info: n_ff = 17408
May 27 21:07:26 tank ollama[3099]: print_info: n_expert = 0
May 27 21:07:26 tank ollama[3099]: print_info: n_expert_used = 0
May 27 21:07:26 tank ollama[3099]: print_info: causal attn = 1
May 27 21:07:26 tank ollama[3099]: print_info: pooling type = 0
May 27 21:07:26 tank ollama[3099]: print_info: rope type = 2
May 27 21:07:26 tank ollama[3099]: print_info: rope scaling = linear
May 27 21:07:26 tank ollama[3099]: print_info: freq_base_train = 1000000.0
May 27 21:07:26 tank ollama[3099]: print_info: freq_scale_train = 1
May 27 21:07:26 tank ollama[3099]: print_info: n_ctx_orig_yarn = 40960
May 27 21:07:26 tank ollama[3099]: print_info: rope_finetuned = unknown
May 27 21:07:26 tank ollama[3099]: print_info: ssm_d_conv = 0
May 27 21:07:26 tank ollama[3099]: print_info: ssm_d_inner = 0
May 27 21:07:26 tank ollama[3099]: print_info: ssm_d_state = 0
May 27 21:07:26 tank ollama[3099]: print_info: ssm_dt_rank = 0
May 27 21:07:26 tank ollama[3099]: print_info: ssm_dt_b_c_rms = 0
May 27 21:07:26 tank ollama[3099]: print_info: model type = 14B
May 27 21:07:26 tank ollama[3099]: print_info: model params = 14.77 B
May 27 21:07:26 tank ollama[3099]: print_info: general.name = Qwen3 14B
May 27 21:07:26 tank ollama[3099]: print_info: vocab type = BPE
May 27 21:07:26 tank ollama[3099]: print_info: n_vocab = 151936
May 27 21:07:26 tank ollama[3099]: print_info: n_merges = 151387
May 27 21:07:26 tank ollama[3099]: print_info: BOS token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOS token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOT token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: PAD token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: LF token = 198 'Ċ'
May 27 21:07:26 tank ollama[3099]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM MID token = 151660 '<|fim_middle|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM REP token = 151663 '<|repo_name|>'
May 27 21:07:26 tank ollama[3099]: print_info: FIM SEP token = 151664 '<|file_sep|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151643 '<|endoftext|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151645 '<|im_end|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151662 '<|fim_pad|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151663 '<|repo_name|>'
May 27 21:07:26 tank ollama[3099]: print_info: EOG token = 151664 '<|file_sep|>'
May 27 21:07:26 tank ollama[3099]: print_info: max token length = 256
May 27 21:07:26 tank ollama[3099]: load_tensors: loading model tensors, this can take a while... (mmap = true)
May 27 21:07:26 tank ollama[3099]: time=2025-05-27T21:07:26.836-05:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model"
May 27 21:07:30 tank ollama[3099]: load_tensors: CPU_Mapped model buffer size = 8840.78 MiB
May 27 21:07:30 tank ollama[3099]: llama_context: constructing llama_context
May 27 21:07:30 tank ollama[3099]: llama_context: n_seq_max = 2
May 27 21:07:30 tank ollama[3099]: llama_context: n_ctx = 8192
May 27 21:07:30 tank ollama[3099]: llama_context: n_ctx_per_seq = 4096
May 27 21:07:30 tank ollama[3099]: llama_context: n_batch = 1024
May 27 21:07:30 tank ollama[3099]: llama_context: n_ubatch = 512
May 27 21:07:30 tank ollama[3099]: llama_context: causal_attn = 1
May 27 21:07:30 tank ollama[3099]: llama_context: flash_attn = 0
May 27 21:07:30 tank ollama[3099]: llama_context: freq_base = 1000000.0
May 27 21:07:30 tank ollama[3099]: llama_context: freq_scale = 1
May 27 21:07:30 tank ollama[3099]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
May 27 21:07:30 tank ollama[3099]: llama_context: CPU output buffer size = 1.20 MiB
May 27 21:07:30 tank ollama[3099]: llama_kv_cache_unified: kv_size = 8192, type_k = 'f16', type_v = 'f16', n_layer = 40, can_shift = 1, padding = 32
May 27 21:07:30 tank ollama[3099]: llama_kv_cache_unified: CPU KV buffer size = 1280.00 MiB
May 27 21:07:30 tank ollama[3099]: llama_kv_cache_unified: KV self size = 1280.00 MiB, K (f16): 640.00 MiB, V (f16): 640.00 MiB
May 27 21:07:30 tank ollama[3099]: llama_context: CPU compute buffer size = 696.01 MiB
May 27 21:07:30 tank ollama[3099]: llama_context: graph nodes = 1526
May 27 21:07:30 tank ollama[3099]: llama_context: graph splits = 1
May 27 21:07:30 tank ollama[3099]: time=2025-05-27T21:07:30.597-05:00 level=INFO source=server.go:630 msg="llama runner started in 4.01 seconds"
May 27 21:08:45 tank ollama[3099]: [GIN] 2025/05/27 - 21:08:45 | 200 | 1m19s | 127.0.0.1 | POST "/api/chat"
May 27 21:13:50 tank ollama[3099]: time=2025-05-27T21:13:50.796-05:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=5.001224659 runner.size="11.2 GiB" runner.vram="11.2 GiB" runner.parallel=2 runner.pid=5382 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e
May 27 21:13:51 tank ollama[3099]: time=2025-05-27T21:13:51.045-05:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=5.250790349 runner.size="11.2 GiB" runner.vram="11.2 GiB" runner.parallel=2 runner.pid=5382 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e
May 27 21:13:51 tank ollama[3099]: time=2025-05-27T21:13:51.295-05:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=5.500354884 runner.size="11.2 GiB" runner.vram="11.2 GiB" runner.parallel=2 runner.pid=5382 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e
OS
Linux
GPU
AMD
CPU
AMD, Intel
Ollama version
0.7.1
What is the issue?
Today, Ollama prompted me to update when I tried to run Qwen3:14b. I ran the oneline install command (
curl -fsSL https://ollama.com/install.sh | sh), and during the install, it said "Nvidia GPU installed.", even though I run an AMD card. Now, whenever I try to run a model, it won't use my gfx card.Right before updating, I observed my GPU being utilized with radeontop. I watched the VRAM fill up, etc. Now, I can see that my Graphics card isn't being utilized at all in radeontop, but my cores all go to 100 in htop - even small models run painfully slow. I am certain that this behavior began immediately after running the install script. (And yes, I have ROCm installed.)
I tried to force the backend, which didn't seem to work:
OLLAMA_GPU_BACKEND=rocm ollama run mymodelI can also verify that my GPU is visible to ROCm, and I have no NVIDIA card in my machine.
Here's what I get when I run
journalctl -u ollama --no-pager --follow --pager-endSo, from what I can tell, Ollama sees my GPU, identifies that there is enough VRAM to hold the model, identifies that rocm is installed, yet makes the conscious choice to try and run the model on my CPU instead.... Unless there something obvious I'm missing, I am pretty sure this is a bug?
Neofetch:
OS: Ubuntu 24.04.2 LTS x86_64
Host: B460MDS3HV2 -CF
Kernel: 6.11.0-26-generic
Uptime: 5 mins
Packages: 3559 (dpkg), 5 (flatpak), 16 (snap)
Shell: bash 5.2.21
Resolution: 2560x1440
DE: GNOME 46.0
WM: Mutter
WM Theme: Adwaita
Theme: Yaru-blue-dark [GTK2/3]
Icons: Yaru-blue [GTK2/3]
Terminal: gnome-terminal
CPU: Intel i7-10700K (16) @ 5.100GHz
GPU: AMD ATI Radeon RX 7600/7600 XT/7600M XT/7600S/7700S / PRO W7600
Memory: 4550MiB / 80346MiB
ollama --version:
ollama version is 0.7.1
Relevant log output
OS
Linux
GPU
AMD
CPU
AMD, Intel
Ollama version
0.7.1