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azzazelx@airozkurwiator:~$ sudo systemctl edit ollama
[sudo] hasło użytkownika azzazelx:
azzazelx@airozkurwiator:~$ ollama pull llama3.1:8b
Error: could not connect to ollama server, run 'ollama serve' to start it
azzazelx@airozkurwiator:~$ sudo systemctl start ollama
azzazelx@airozkurwiator:~$ ollama pull llama3.1:8b
pulling manifest
pulling 667b0c1932bc: 100% ▕████████████████████████████████████████████████▏ 4.9 GB
pulling 948af2743fc7: 100% ▕████████████████████████████████████████████████▏ 1.5 KB
pulling 0ba8f0e314b4: 100% ▕████████████████████████████████████████████████▏ 12 KB
pulling 56bb8bd477a5: 100% ▕████████████████████████████████████████████████▏ 96 B
pulling 455f34728c9b: 100% ▕████████████████████████████████████████████████▏ 487 B
verifying sha256 digest
writing manifest
success
azzazelx@airozkurwiator:~$ sudo systemctl cat ollama | grep -i vulkan
azzazelx@airozkurwiator:~$ sudo systemctl edit ollama
azzazelx@airozkurwiator:~$ sudo systemctl stop ollama
azzazelx@airozkurwiator:~$ sudo systemctl disable ollama
azzazelx@airozkurwiator:~$ nano ~/.bashrc
azzazelx@airozkurwiator:~$ source ~/.bashrc
azzazelx@airozkurwiator:~$ ollama-start
time=2026-04-23T00:19:45.456+01:00 level=INFO source=routes.go:1752 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GGML_VK_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:0 OLLAMA_DEBUG:INFO OLLAMA_DEBUG_LOG_REQUESTS:false OLLAMA_EDITOR: OLLAMA_FLASH_ATTENTION:true OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE:q8_0 OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/home/azzazelx/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NO_CLOUD: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 OLLAMA_VULKAN:true ROCR_VISIBLE_DEVICES: http_proxy: https_proxy: no_proxy:]"
time=2026-04-23T00:19:45.456+01:00 level=INFO source=routes.go:1754 msg="Ollama cloud disabled: false"
time=2026-04-23T00:19:45.474+01:00 level=INFO source=images.go:517 msg="total blobs: 0"
time=2026-04-23T00:19:45.474+01:00 level=INFO source=images.go:524 msg="total unused blobs removed: 0"
time=2026-04-23T00:19:45.474+01:00 level=INFO source=routes.go:1810 msg="Listening on 127.0.0.1:11434 (version 0.21.0)"
time=2026-04-23T00:19:45.475+01:00 level=INFO source=runner.go:67 msg="discovering available GPUs..."
time=2026-04-23T00:19:45.476+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 37007"
time=2026-04-23T00:19:46.696+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 41407"
time=2026-04-23T00:19:46.723+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 44039"
time=2026-04-23T00:19:46.752+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 44635"
time=2026-04-23T00:19:46.817+01:00 level=INFO source=types.go:42 msg="inference compute" id=00000000-c600-0000-0000-000000000000 filter_id="" library=Vulkan compute=0.0 name=Vulkan0 description="AMD Radeon 780M Graphics (RADV PHOENIX)" libdirs=ollama,vulkan driver=0.0 pci_id=0000:c6:00.0 type=iGPU total="96.0 GiB" available="95.4 GiB"
time=2026-04-23T00:19:46.817+01:00 level=INFO source=routes.go:1860 msg="vram-based default context" total_vram="96.0 GiB" default_num_ctx=262144
time=2026-04-23T00:19:59.626+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 35199"
llama_model_loader: loaded meta data with 29 key-value pairs and 292 tensors from /home/azzazelx/.ollama/models/blobs/sha256-667b0c1932bc6ffc593ed1d03f895bf2dc8dc6df21db3042284a6f4416b06a29 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Meta Llama 3.1 8B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Meta-Llama-3.1
llama_model_loader: - kv 5: general.size_label str = 8B
llama_model_loader: - kv 6: general.license str = llama3.1
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 9: llama.block_count u32 = 32
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 4096
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: general.file_type u32 = 15
llama_model_loader: - kv 18: llama.vocab_size u32 = 128256
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 21: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 27: tokenizer.chat_template str = {{- bos_token }}n{%- if custom_tools ...
llama_model_loader: - kv 28: general.quantization_version u32 = 2
llama_model_loader: - type f32: 66 tensors
llama_model_loader: - type q4_K: 193 tensors
llama_model_loader: - type q6_K: 33 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 4.58 GiB (4.89 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 1
print_info: no_alloc = 0
print_info: model type = ?B
print_info: model params = 8.03 B
print_info: general.name = Meta Llama 3.1 8B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128009 '<|eot_id|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2026-04-23T00:20:00.044+01:00 level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=262144 n_ctx_train=131072
time=2026-04-23T00:20:00.044+01:00 level=INFO source=server.go:444 msg="starting runner" cmd="/usr/local/bin/ollama runner --model /home/azzazelx/.ollama/models/blobs/sha256-667b0c1932bc6ffc593ed1d03f895bf2dc8dc6df21db3042284a6f4416b06a29 --port 37467"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=sched.go:484 msg="system memory" total="78.3 GiB" free="75.7 GiB" free_swap="512.0 MiB"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=sched.go:491 msg="gpu memory" id=00000000-c600-0000-0000-000000000000 library=Vulkan available="94.9 GiB" free="95.3 GiB" minimum="457.0 MiB" overhead="0 B"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=server.go:511 msg="loading model" "model layers"=33 requested=-1
time=2026-04-23T00:20:00.045+01:00 level=INFO source=device.go:240 msg="model weights" device=Vulkan0 size="4.3 GiB"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=device.go:251 msg="kv cache" device=Vulkan0 size="8.0 GiB"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=device.go:262 msg="compute graph" device=Vulkan0 size="8.3 GiB"
time=2026-04-23T00:20:00.045+01:00 level=INFO source=device.go:272 msg="total memory" size="20.6 GiB"
time=2026-04-23T00:20:00.061+01:00 level=INFO source=runner.go:965 msg="starting go runner"
load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-icelake.so
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = AMD Radeon 780M Graphics (RADV PHOENIX) (radv) | uma: 1 | fp16: 1 | bf16: 0 | warp size: 64 | shared memory: 65536 | int dot: 1 | matrix cores: KHR_coopmat
load_backend: loaded Vulkan backend from /usr/local/lib/ollama/vulkan/libggml-vulkan.so
time=2026-04-23T00:20:00.097+01:00 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.AVX512=1 CPU.0.AVX512_VBMI=1 CPU.0.AVX512_VNNI=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(gcc)
time=2026-04-23T00:20:00.098+01:00 level=INFO source=runner.go:1001 msg="Server listening on 127.0.0.1:37467"
time=2026-04-23T00:20:00.101+01:00 level=INFO source=runner.go:895 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:131072 KvCacheType:q8_0 NumThreads:8 GPULayers:33[ID:00000000-c600-0000-0000-000000000000 Layers:33(0..32)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
time=2026-04-23T00:20:00.104+01:00 level=INFO source=server.go:1364 msg="waiting for llama runner to start responding"
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon 780M Graphics (RADV PHOENIX)) (0000:c6:00.0) - 97611 MiB free
time=2026-04-23T00:20:00.104+01:00 level=INFO source=server.go:1398 msg="waiting for server to become available" status="llm server loading model"
llama_model_loader: loaded meta data with 29 key-value pairs and 292 tensors from /home/azzazelx/.ollama/models/blobs/sha256-667b0c1932bc6ffc593ed1d03f895bf2dc8dc6df21db3042284a6f4416b06a29 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Meta Llama 3.1 8B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Meta-Llama-3.1
llama_model_loader: - kv 5: general.size_label str = 8B
llama_model_loader: - kv 6: general.license str = llama3.1
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 9: llama.block_count u32 = 32
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 4096
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: general.file_type u32 = 15
llama_model_loader: - kv 18: llama.vocab_size u32 = 128256
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 21: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 27: tokenizer.chat_template str = {{- bos_token }}n{%- if custom_tools ...
llama_model_loader: - kv 28: general.quantization_version u32 = 2
llama_model_loader: - type f32: 66 tensors
llama_model_loader: - type q4_K: 193 tensors
llama_model_loader: - type q6_K: 33 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 4.58 GiB (4.89 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 131072
print_info: n_embd = 4096
print_info: n_embd_inp = 4096
print_info: n_layer = 32
print_info: n_head = 32
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 4
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-05
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 14336
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: n_expert_groups = 0
print_info: n_group_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 131072
print_info: rope_yarn_log_mul= 0.0000
print_info: rope_finetuned = unknown
print_info: model type = 8B
print_info: model params = 8.03 B
print_info: general.name = Meta Llama 3.1 8B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128009 '<|eot_id|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = false)
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
load_tensors: offloading 32 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 33/33 layers to GPU
load_tensors: Vulkan0 model buffer size = 4403.49 MiB
load_tensors: Vulkan_Host model buffer size = 281.81 MiB
ggml_backend_vk_get_device_memory called: uuid 00000000-c600-0000-0000-000000000000
ggml_backend_vk_get_device_memory called: luid 0x0000000000000000
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 131072
llama_context: n_ctx_seq = 131072
llama_context: n_batch = 512
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = enabled
llama_context: kv_unified = false
llama_context: freq_base = 500000.0
llama_context: freq_scale = 1
llama_context: Vulkan_Host output buffer size = 0.50 MiB
llama_kv_cache: Vulkan0 KV buffer size = 8704.00 MiB
llama_kv_cache: size = 8704.00 MiB (131072 cells, 32 layers, 1/1 seqs), K (q8_0): 4352.00 MiB, V (q8_0): 4352.00 MiB
llama_context: Vulkan0 compute buffer size = 412.01 MiB
llama_context: Vulkan_Host compute buffer size = 264.02 MiB
llama_context: graph nodes = 999
llama_context: graph splits = 2
time=2026-04-23T00:20:06.885+01:00 level=INFO source=server.go:1402 msg="llama runner started in 6.84 seconds"
time=2026-04-23T00:20:06.885+01:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-04-23T00:20:06.885+01:00 level=INFO source=server.go:1364 msg="waiting for llama runner to start responding"
time=2026-04-23T00:20:06.885+01:00 level=INFO source=server.go:1402 msg="llama runner started in 6.84 seconds"
[GIN] 2026/04/23 - 00:22:38 | 200 | 2m39s | 127.0.0.1 | POST "/api/generate"

azzazelx@airozkurwiator:~$ curl -s http://localhost:11434/api/generate -d '{
"model": "llama3.1:8b",
"prompt": "napisz długie opowiadanie o kocie",
"stream": false
}' | python3 -c "
import json,sys
d=json.load(sys.stdin)
toks=d['eval_count']
secs=d['eval_duration']/1e9
print(f'Predkosc: {toks/secs:.1f} tok/s')
"
Predkosc: 13.9 tok/s
azzazelx@airozkurwiator:~$ ^C
azzazelx@airozkurwiator:~$


     
 
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