Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 maja 2024
Dedykowany model do generowania kodu od Mistral, wytrenowany na ogromnym korpusie programistycznym obejmującym 80+ języków. Wyróżnia się uzupełnianiem Fill-in-the-Middle (FIM) — kluczową techniką zasilającą autouzupełnianie IDE. Integruje się natywnie z VS Code przez continue.dev i Cursor.
| Licence | What it permits | Applies to |
|---|---|---|
MNPL-0.1 | Research / non-commercial only Research / non-commercial only — this licence does NOT permit shipping a commercial product. | Codestral 22B |
| Codestral 22B | Min 14 GB VRAM · Q4_K_M · 32,768 ctx · ollama run codestral:22b |
The cheapest GPU that runs Codestral locally (min 14 GB VRAM) is the AMD Radeon RX 9060 XT 16GB (16 GB).
Install Ollama then run: ollama run codestral:22b
Minimum VRAM: 14 GB. For best results use Q4_K_M quantization.
Codestral needs about 14 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Codestral 22B (14 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Codestral runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
Q4_K_M is the best balance of quality and VRAM for Codestral in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Install Ollama, then run: ollama run codestral:22b. This downloads Codestral and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.