RUNTIME / ADVANCED
vLLM
Linux GPU servers, concurrency and OpenAI-compatible production APIs
Source primaireDifficultyAdvancedSetup profile
Platforms3nvidia · amd · intel
APIOpenAI-compatible server:8000
01 / INSTALL & RUN
- 1Install
uv pip install vllm --torch-backend=auto - 2Start a model
vllm serve google/gemma-3-1b-it --dtype auto - 3Connect your app
OpenAI-compatible server · :8000. Keep the service bound to localhost unless you add authentication and network controls.
Attention
CUDA, ROCm and XPU feature coverage differs. Driver, shared-memory and quantization compatibility are version-specific.
02 / COMPATIBLE MODELS
Modèles open-weight représentatifs
Google
Gemma 3 1B
1BINT4 / GGUF Q4
- Mémoire estimée
- ~1.4 GB
- Contexte
- 32K
Meta
Llama 3.2 3B
3BGGUF Q4
- Mémoire estimée
- ~2.8 GB
- Contexte
- 128K
Alibaba Qwen
Qwen3 4B
4BGGUF Q4
- Mémoire estimée
- ~3.6 GB
- Contexte
- 32K+
Google
Gemma 3 4B
4BINT4 / GGUF Q4
- Mémoire estimée
- ~4.2 GB
- Contexte
- 128K
Alibaba Qwen
Qwen3 8B
8BGGUF Q4
- Mémoire estimée
- ~6.8 GB
- Contexte
- 32K+
Google
Gemma 3 12B
12BINT4
- Mémoire estimée
- ~9.4 GB
- Contexte
- 128K