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" } ----------