DevRadar
Back to Tools

Codestral

CLI AgentFreemium

Best for: Enterprises requiring data sovereignty and local deployment, High-frequency IDE code completion, Agentic multi-file refactoring, Regulated industries like defense and finance

Last updated: Jan 8, 2026

Capabilities

9/13 supported

Web Frontend

Build React, Vue, or other frontend applications

Web Backend

Create APIs, server-side logic, and backend services

Mobile Apps

Build native or cross-platform mobile applications

SSR / SEO

Server-side rendering for better SEO performance

Database

Integrate and manage database connections

Deployment

Deploy and host applications automatically

Agentic Mode

Autonomous multi-step task execution

Chat Interface

Interactive conversational AI assistant

Code Generation

Generate code from natural language prompts

Debugging

Identify and fix bugs automatically

Terminal Access

Execute commands in the terminal

Web Browsing

Browse the web for information

Test Generation

Generate unit and integration tests

Technical Analysis

Codestral is Mistral AI's first dedicated code model, featuring a 22B parameter architecture that strikes a balance between raw intelligence and inference speed. It excels at Fill-In-the-Middle (FIM) tasks, which is critical for low-latency IDE autocomplete. Because it is available as open weights, it has become the gold standard for self-hosted AI coding assistants in environments where data privacy is non-negotiable, such as finance or defense.

The model’s performance on benchmarks like HumanEval and MBPP is competitive with much larger proprietary models. However, its true power lies in its 32k context window and agentic capabilities, allowing it to reason across multiple files. While it provides a cheaper token-per-performance ratio via API, running the full 22B model locally requires significant hardware, typically an RTX 3090/4090 or Mac Studio, to achieve usable tokens-per-second for real-time completion.

Limitations & Considerations

Known Limitations

  • Local inference of 22B models requires high-end consumer GPUs (e.g., RTX 4090)
  • Agentic workflows can consume large amounts of tokens despite low per-token pricing
  • HumanEval scores slightly trail the most expensive proprietary frontier models

Frequently Asked Questions

Get Started

Architecture isn't a gamble.
It's a calculation.

Eliminate incompatible technologies and build a defensible tech stack.

No assumptions. No account required. Deterministic validation.