Devstral 2
Devstral 2
📌 Model Overview
Mistral's coding-agent model for repository work, terminal tasks, and software fixes
Devstral 2 is a Open Weights model developed by Mistral AI, released on 2025-12-09. It is designed primarily for Chat Reasoning workloads. Featuring a 262K tokens context window and Undisclosed parameter count, it offers robust performance for enterprise integration, developers, and researchers.
✨ Key Features & Capabilities
| Feature | Description |
|---|---|
| Context Window | 262K tokens capacity for extended prompts and multi-turn workflows |
| Primary Task | Optimized for Chat Reasoning |
| Deployment | self-hostable, api-only |
| Modality | text |
| Max Output | Max Output: 262K tokens |
| Tool / function calling support | Tool / function calling support |
⚙️ Technical Specifications
| Specification | Details |
|---|---|
| Developer / Lab | Mistral AI |
| Release Date | 2025-12-09 |
| Model Type | Open Weights |
| Parameters | Undisclosed |
| Context Window | 262K tokens |
| License | Apache-2.0 |
| Model Family | devstral |
📊 Benchmarks & Performance
| Benchmark | Score | Source |
|---|---|---|
| Artificial Analysis Coding Index | 23.7 (index) | Independent Eval |
| SciCode | 33.1% | Independent Eval |
| Terminal-Bench Hard | 18.9% | Independent Eval |
💰 Pricing
| Tier / Unit | Rate (USD) |
|---|---|
| 1M input tokens | $0.4 |
| 1M output tokens | $2 |
🔗 Resources & Links
| Resource | Link |
|---|---|
| Hugging Face | https://huggingface.co/mistralai/Devstral-2-123B-Instruct-2512 |
📜 License & Usage
This model is governed by the Apache-2.0 license. Please check official developer guidelines before commercial deployment.
Key Features
Max Output: 262K tokens
Tool / function calling support
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Verified Sources
Tags
Model Specs
Parameters
Undisclosed
Context Window
262K tokens
License
Apache-2.0
Deployment
Pricing
- 1M input tokens$0.4
- 1M output tokens$2
as of 2026-07-26
Resources & Links
Lineage
Curator Notes
Skeleton entry imported from models.dev backfill (2026-07-26). Needs manual enrichment and primary-source verification.
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