作者： Jakub Rusinowski · 最后更新： 2026年7月10日
Mistral's latest small model, now with vision capabilities and Apache 2.0 license. Mistral Small 3.1 24B features a 128k context window (4× larger than its predecessor), multimodal image understanding, and relicensed to Apache 2.0 for full commercial use — while outperforming Gemma 3 27B on most benchmarks.
| Mistral Small 3.1 24B | Min 14 GB VRAM · Q4_K_M · 128,000 ctx · ollama run mistral-small3.1 |
The cheapest GPU that runs Mistral Small 3.1 locally (min 14 GB VRAM) is the AMD Radeon RX 9060 XT 16GB (16 GB).
Install Ollama then run: ollama run mistral-small3.1
Minimum VRAM: 14 GB. For best results use Q4_K_M quantization.
Mistral Small 3.1 needs about 14 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Mistral Small 3.1 24B (14 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Mistral Small 3.1 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 Mistral Small 3.1 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 mistral-small3.1. This downloads Mistral Small 3.1 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.