Devstral — Local AI Model by Mistral AI

Written by Jakub Rusinowski · Last updated September 11, 2026

Mistral AI's coding specialists, spanning both generations. The original Devstral Small 2505 posts 46.8% on SWE-Bench Verified; its December 2025 successor Devstral Small 2 lifts that to 68.0% at the same 24B, which is the local-agent sweet spot — about 15 GB at Q4_K_M on one consumer card. The 123B flagship reaches 71.6%. Built for agentic software engineering: multi-file editing, repo navigation, and test-driven development. Apache 2.0 throughout.

Licence

Licence	What it permits	Applies to
`Apache-2.0`	Commercial use permitted Commercial use permitted. No usage restrictions beyond attribution.	Devstral-2 123B, Devstral-2 22B (Unverified Listing), Devstral Small 2505 24B, Devstral Small 2 24B

Hardware Requirements

Devstral-2 123B	Min 75 GB VRAM · Q4_K_M · 262,144 ctx · `ollama run devstral:123b`
Devstral-2 22B (Unverified Listing)	Min 14 GB VRAM · Q4_K_M · 128,000 ctx ·
Devstral Small 2505 24B	Min 15 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run devstral:24b`
Devstral Small 2 24B	Min 15 GB VRAM · Q4_K_M · 262,144 ctx · `ollama run devstral-small-2:24b`

Recommended GPU

The cheapest GPU that runs Devstral locally (min 14 GB VRAM) is the AMD Radeon RX 9060 XT 16GB (16 GB).

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AMD Radeon RX 9060 XT 16GB

16 GB VRAM · 160 W board power

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How to Run Locally

Install Ollama then run: ollama run devstral:123b

Minimum VRAM: 14 GB. For best results use Q4_K_M quantization.

Devstral — Frequently Asked Questions

How much VRAM does Devstral need?

Devstral needs about 14 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Devstral-2 123B (75 GB, Q4_K_M); Devstral-2 22B (Unverified Listing) (14 GB, Q4_K_M); Devstral Small 2505 24B (15 GB, Q4_K_M); Devstral Small 2 24B (15 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Devstral on an RTX 4090 (24 GB)?

Yes — Devstral 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.

What quantization should I use for Devstral?

Q4_K_M is the best balance of quality and VRAM for Devstral 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.

How do I run Devstral with Ollama?

Install Ollama, then run: ollama run devstral:123b. This downloads Devstral and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.