Mistral AI · 24B · Dense
Coding-focused model with 256K context — 68% SWE-bench Check if your GPU or Mac can run Devstral Small 2 24B locally — 13.4 GB min, 22.4 GB recommended.
| Quant | Bits | VRAM | Quality | Status |
|---|---|---|---|---|
| Q2_K | 2 | 8.2 GB | low | — |
| Q3_K_M | 3 | 11.3 GB | moderate | — |
| Q4_K_M | 4 | 12.8 GB | good | — |
| Q5_K_M | 5 | 15.9 GB | good | — |
| Q6_K | 6 | 18.9 GB | excellent | — |
| Q8_0 | 8 | 25.1 GB | excellent | — |
| F16 | 16 | 49.7 GB | lossless | — |
About this model
Note: this model requires Ollama 0.13.3 or later. Download Ollama
Devstral Small 2
Devstral is an agentic LLM for software engineering tasks. Devstral 2 models excel at using tools to explore codebases, editing multiple files and power software engineering agents.
The model achieves remarkable performance on SWE-bench.
ollama run devstral-small-2
Key Features
The Devstral 2 Instruct model offers the following capabilities:
Agentic Coding: Devstral is designed to excel at agentic coding tasks, making it a great choice for software engineering agents.
Improved Performance: Devstral 2 is a step-up compared to its predecessors.
Better Generalization: Generalises better to diverse prompts and coding environments.
Use Cases
AI Code Assistants, Agentic Coding, and Software Engineering Tasks. Leveraging advanced AI capabilities for complex tool integration and deep codebase understanding in coding environments.
Benchmark Results
| Model/Benchmark | Size (B Tokens) | SWE Bench Verified | SWE Bench Multilingual | Terminal Bench |
|---|---|---|---|---|
| Devstral 2 | 123 | 72.2% | 61.3% | 40.5% |
| Devstral Small 2 | 24 | 65.8% | 51.6% | 32.0% |
| DeepSeek v3.2 | 671 | 73.1% | 70.2% | 46.4% |
| Kimi K2 Thinking | 1000 | 71.3% | 61.1% | 35.7% |
| MiniMax M2 | 230 | 69.4% | 56.5% | 30.0% |
| GLM 4.6 | 455 | 68.0% | – | 40.5% |
| Qwen 3 Coder Plus | 480 | 69.6% | 54.7% | 37.5% |
| Gemini 3 Pro | – | 76.2% | – | 54.2% |
| Claude Sonnet 4.5 | – | 77.2% | 68.0% | 42.8% |
| GPT 5.1 Codex Max | – | 77.9% | – | 58.1% |
| GPT 5.1 Codex High | – | 73.7% | – | 52.8% |
License
Apache 2.0
Reference
Can I run Devstral Small 2 24B locally?
- Can I run Devstral Small 2 24B locally?
- Devstral Small 2 24B needs about 13.4 GB of memory at a minimum and 22.4 GB recommended. Open this page to grade it against your GPU or Mac, then run it with runai, Ollama or LM Studio.
- How much VRAM does Devstral Small 2 24B need?
- At Q4_K_M, Devstral Small 2 24B uses about 12.8 GB of VRAM. Higher quants need more memory; lower quants fit tighter cards with a quality tradeoff.