개요
자동으로 GPU/CPU/RAM을 감지하고, 벤치마크 테스트 품질과 속도에 따라 HuggingFace 모델의 순위를 매깁니다. 하드웨어 시뮬레이션, JSON 출력 및 즉시 채팅을 지원합니다.
README 미리보기
# whichllm\n\n[](https://pypi.org/project/whichllm/)\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n[](https://github.com/Andyyyy64/whichllm/actions/workflows/test.yml)\n[](https://github.com/sponsors/Andyyyy64)\n\n**Find the best local LLM that actually runs on your hardware.**\n\nAuto-detects your GPU/CPU/RAM and ranks the top models from HuggingFace that fit your system.\n\n[日本語版はこちら](docs/README.ja.md)\n\n## Quick start\n\nRun the recommendation command once, with no project setup.\n\n```bash\nuvx whichllm@latest\n```\n\nSimulate a GPU before you buy hardware.\n\n```bash\nuvx whichllm@latest --gpu "RTX 4090"\n```\n\nInstall it when you use it often.\n\n```bash\nuv tool install whichllm\nuv tool upgrade whichllm # update an existing install\n```\n\nOther install paths.\n\n```bash\nbrew install andyyyy64/whichllm/whichllm\npip install whichllm\n```\n\n## Common workflows\n\nAfter install, run `whichllm` directly. For one-off runs, replace `whichllm`\nwith `uvx whichllm@latest`.\n\n```bash\n# Best models for this machine\nwhichllm\n\n# Pretend you have a specific GPU\nwhichllm --gpu "RTX 4090"\n\n# Compare upgrade candidates\nwhichllm upgrade "RTX 4090" "RTX 5090" "H100"\n\n# Find the GPU needed for a model\nwhichllm plan "llama 3 70b"\n\n# Start a chat with a model\nwhichllm run "qwen 2.5 1.5b gguf"\n\n# Print copy-paste Python\nwhichllm snippet "qwen 7b"\n\n# Return JSON for scripts\nwhichllm --top 1 --json\n```\n\n\n\n## See it\n\n```text\n$ whichllm --gpu "RTX 4090"\n\n#1 Qwen/Qwen3.6-27B 27.8B Q5_K_M score 92.8 27 t/s\n#2 Qwen/Qwen3-32B 32.0B Q4_K_M score 83.0 31 t/s\n#3 Qwen/Qwen3-30B-A3B 30.0B Q5_K_M score 82.7 102 t/s\n```\n\nThe 32B model **fits your card fine** — whichllm still ranks the 27B #1,\nbecause it scores higher on real benchmarks and is a newer generation.\nA size-only "what fits?" tool would hand you the bigger one. That gap is\nthe whole point of whichllm. (Note #3: a MoE model