The most cost-effective specialized code model for production developer tooling with serious context capacity.
High-volume code generation, completion, and refactoring tasks where cost efficiency and long-context handling matter most.
Exceptionally low cost at $0.30/$0.90 per 1M tokens — far cheaper than GPT-4.1 or Claude Sonnet 4.5 for code tasks
256K context window enables full large codebase ingestion, making repo-level refactoring and code review practical
Purpose-built for code: trained across 80+ languages with strong fill-in-the-middle (FIM) completion support for IDE autocomplete
Meaningful upgrade over Codestral 25.01 with improved instruction following and multi-file reasoning
See what Mistral: Codestral 2508 actually costs at your usage level
Based on Mistral: Codestral 2508 API pricing: $0.3/1M input · $0.8999999999999999/1M output. Real costs vary by provider discounts and caching. Check the provider for exact current rates.
Price History
→0% since May 9
4 data points · tracked daily since May 9, 2026
High-volume code generation, completion, and refactoring tasks where cost efficiency and long-context handling matter most.. Start free — no card required.
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Devstral 2 2512 is Mistral's second-generation code-specialized model, built specifically for software development tasks with a 256K context window. It targets developers needing a cost-efficient coding assistant without sacrificing meaningful capability.
Pricing moves, ranking shifts, and capability updates.
Mistral: Codestral 2508 (Mistral) is now indexed. It supersedes Codestral 25.01. The most cost-effective specialized code model for production developer tooling with serious context capacity.
View modelMistral: Codestral 2508 is best for high-volume code generation, completion, and refactoring tasks where cost efficiency and long-context handling matter most.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and fast speed.
You need a model that handles general reasoning, writing, or multimodal inputs alongside code — a generalist like Claude Sonnet 4.5 or Gemini 2.5 Pro will serve you better.
Meta: Llama 3.1 8B Instruct is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
Mistral: Ministral 3 14B 2512 is the better pick when response time matters more than maximum depth or premium quality.
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You need a model that handles general reasoning, writing, or multimodal inputs alongside code — a generalist like Claude Sonnet 4.5 or Gemini 2.5 Pro will serve you better.
Non-coding tasks like long-form writing, analysis, or research are outside its training focus and noticeably weaker than general-purpose models
No multimodal support — cannot process images, diagrams, or screenshots of code
Lags behind GPT-4.1 and Claude Sonnet 4.5 on complex algorithmic reasoning and competitive programming benchmarks
Devstral Small 1.1 is Mistral's code-specialized small model, purpose-built for software engineering tasks including code generation, debugging, and repository-level reasoning. It succeeds Devstral Small 1.0 with improved instruction following and agentic coding capabilities at a fraction of flagship model costs.
Ministral 3B is Mistral's compact edge-optimized model designed for high-throughput, low-latency tasks at an extremely competitive price point. Despite its small size, it supports a 262K context window, making it unusually capable for a sub-$0.20/1M token model.
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