Fred'ô farias06

Ma configuration :

• Proxmox : 8.4.1 ( kernel : Linux 6.8.12-10-pve (2025-04-18T07:39Z) )
• VM sous Ubuntu : Ubuntu 22.04.5 LTS ( kernel : 5.15.0-140-generic )
  • Ollama : 0.9.0 ( Le 10/02/2025 : 0.5.7 )  : https://ollama.com/
  • Python : 3.10 (pour AUTOMATIC1111) & 3.11 (pour Ollama)
  • Open WebUI : 0.6.13 : https://github.com/open-webui/open-webui
  • NVIDIA : 575.51.03 .( Le 10/02/2025  : 570.86.15 )
  • CUDA : 12.8.93 ( nvcc –version )
  • AUTOMATIC1111 : 1.10.1 : https://github.com/AUTOMATIC1111/stable-diffusion-webui

J’ai lancé un nouveau test via llm_benchmark, afin de comparer avec ma dernière configuration fonctionnelle :

J’ai changé la carte NVIDIA car deux cartes NVIDIA avec 8 Go chacune, elles sont vues par la VM qui est lancé par proxmox :

# nvidia-smi --list-gpus
GPU 0: Quadro M5000 (UUID: GPU-)
GPU 1: Quadro M4000 (UUID: GPU-)
# nvidia-smi      
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.86.15              Driver Version: 570.86.15      CUDA Version: 12.8     |
|-----------------------------------------+------------------------+----------------------+
| 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  Quadro M5000                   Off |   00000000:00:10.0 Off |                  Off |
| 38%   37C    P8             13W /  150W |       5MiB /   8192MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   1  Quadro M4000                   Off |   00000000:00:11.0 Off |                  N/A |
| 46%   39C    P8             13W /  120W |       5MiB /   8192MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

les résultats du test sont les suivants :

J’ai trouvé un outil de test de llm : llm_benchmark ( installation via pip )

• https://pypi.org/project/llm-benchmark/
• https://github.com/aidatatools/ollama-benchmark
• https://llm.aidatatools.com/

Je suis en dernière position : https://llm.aidatatools.com/results-linux.php , avec “llama3.1:8b”: “1.12”.

 llm_benchmark run
-------Linux----------
{'id': '0', 'name': 'Quadro 4000', 'driver': '390.157', 'gpu_memory_total': '1985.0 MB',
'gpu_memory_free': '1984.0 MB', 'gpu_memory_used': '1.0 MB', 'gpu_load': '0.0%', 
'gpu_temperature': '60.0°C'}
Only one GPU card
Total memory size : 61.36 GB
cpu_info: Intel(R) Xeon(R) CPU E5-2450 v2 @ 2.50GHz
gpu_info: Quadro 4000
os_version: Ubuntu 22.04.5 LTS
ollama_version: 0.5.7
----------
LLM models file path：/usr/local/lib/python3.10/dist-packages/llm_benchmark/data/benchmark_models_16gb_ram.yml
Checking and pulling the following LLM models
phi4:14b
qwen2:7b
gemma2:9b
mistral:7b
llama3.1:8b
llava:7b
llava:13b
----------
....
----------------------------------------
Sending the following data to a remote server
-------Linux----------
{'id': '0', 'name': 'Quadro 4000', 'driver': '390.157', 'gpu_memory_total': '1985.0 MB',
 'gpu_memory_free': '1984.0 MB', 'gpu_memory_used': '1.0 MB', 'gpu_load': '0.0%', 
'gpu_temperature': '61.0°C'}
Only one GPU card
-------Linux----------
{'id': '0', 'name': 'Quadro 4000', 'driver': '390.157', 'gpu_memory_total': '1985.0 MB',
 'gpu_memory_free': '1984.0 MB', 'gpu_memory_used': '1.0 MB', 'gpu_load': '0.0%',
 'gpu_temperature': '61.0°C'}
Only one GPU card
{
    "mistral:7b": "1.40",
    "llama3.1:8b": "1.12",
    "phi4:14b": "0.76",
    "qwen2:7b": "1.31",
    "gemma2:9b": "1.03",
    "llava:7b": "1.84",
    "llava:13b": "0.73",
    "uuid": "",
    "ollama_version": "0.5.7"
}
----------