Mistral AI · 24B · Densa
Coding-focused model with 256K context — 68% SWE-bench Comprueba si tu GPU o Mac puede ejecutar Devstral Small 2 24B localmente — 13.4 GB mínimo, 22.4 GB recomendado.
| Cuant | Bits | VRAM | Calidad | Estado |
|---|---|---|---|---|
| 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 | — |
Sobre este modelo
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
¿Puedo ejecutar Devstral Small 2 24B localmente?
- ¿Puedo ejecutar Devstral Small 2 24B localmente?
- Devstral Small 2 24B necesita alrededor de 13.4 GB de memoria como mínimo y 22.4 GB recomendados. Abre esta página para evaluarlo con tu GPU o Mac, y luego ejecútalo con runai, Ollama o LM Studio.
- ¿Cuánta VRAM necesita Devstral Small 2 24B?
- En Q4_K_M, Devstral Small 2 24B usa aproximadamente 12.8 GB de VRAM. Cuantizaciones más altas necesitan más memoria; las más bajas caben en tarjetas más ajustadas con una pérdida de calidad.