RUNTIME / MEDIUM
llama.cpp
GGUF models, CPU/GPU offload, embedded and unusual hardware
Source primaireDifficultyMediumSetup profile
Platforms5cpu · apple · nvidia · amd · intel
APIOpenAI-compatible server:9931 default
01 / INSTALL & RUN
Installation depends on your OS. These commands are examples or templates: replace placeholders and verify quantization, file format, drivers and runtime support. Memory fit does not guarantee deployment.
- 1Install
brew install llama.cpp # or use upstream binaries - 2Start a model
llama-server -m <downloaded-model.gguf> --ctx-size <verified-context> --port 9931 - 3Connect your app
OpenAI-compatible server · :9931 default. Keep the service bound to localhost unless you add authentication and network controls.
Attention
New architectures may require a recent build. Backend availability does not imply equal performance. Since v0.7.0 (2026-10-15) llama-server listens on port 9931 by default instead of 8080; the example commands pin that port explicitly. Older builds accept the same --port flag but default to 8080.
02 / COMPATIBLE MODELS
Modèles open-weight représentatifs
Alibaba Qwen
Qwen3.6 27B
27BQ4 / NVFP4 estimate
- Mémoire estimée
- ~18.5 GB
- Contexte
- 262K native
Alibaba Qwen
Qwen3.8 27B
27BQ4 estimate
- Mémoire estimée
- ~19.5 GB
- Contexte
- 262K native
Alibaba Qwen
Qwen3.6 35B-A3B
35B3B active · Q4 / NVFP4 MoE
- Mémoire estimée
- ~25 GB
- Contexte
- 262K native
DeepSeek
DeepSeek V4 Flash
284B13B active · Official FP4 + FP8 mixed
- Mémoire estimée
- ~176 GB
- Contexte
- 1M native
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