AI model by Mistral AI
Codestral 25.08 for business
Mistral's low-latency coding model for code completion and generation, with fill-in-the-middle support, tool calling and a 128K window.
- Reviewed on September 24, 2026
- Mistral AI
Capability tiersRelative, not benchmarks
Key facts about Codestral 25.08
- Model ID at review
- codestral-2508
- Provider
- Mistral AI
- Main category
- Coding
- Open weights
- No, available as a hosted service
- Last reviewed
- September 24, 2026
Fit
Where it fits and where it does not
Good at
-
Fast code completion inside editors.
-
Fill-in-the-middle, completing code between existing lines.
-
Generating functions and tests.
-
Tool calling and structured outputs.
-
Low cost per request.
Not the right choice for
-
Large, multi-file agent changes, where bigger models do better.
-
Image input.
-
Self-hosting, since it is not listed as open weight.
-
General business chat.
Use cases
Business use cases we would use it for
Editor completion
Test drafting
Query helpers
Our notes
When we would choose it
Codestral 25.08 is Mistral's current Codestral model, released in July 2025. It is built for low-latency code completion and generation, including fill-in-the-middle, where the model completes code between existing lines rather than only at the end. It supports tool calling and structured outputs, and the official card lists a 128K token context window.
Speed matters for code completion. A suggestion that arrives while the developer is still typing is useful. One that arrives two seconds later is ignored. That is why smaller, faster coding models still have a place next to large models such as Claude Opus or GPT-6 Sol.
For larger tasks, such as changing a feature across many files, we would use a stronger model in an agent setup and keep Codestral for completion. In our own work, every AI-generated change is reviewed by an engineer. See AI-accelerated development.
Codestral is listed under Mistral's commercial license rather than as open weights, so it is used through the API. If you need a coding model you can host yourself, look at Qwen3-Coder or Mistral Small 4.
When building completion into an internal tool, we would measure acceptance rate: how often developers keep the suggestion. It is the simplest and most honest measure of whether a coding model helps, and it is easy to track over time. See AI copilots.
Before you commit
Things to check before you commit
-
Context
The official card lists 128K tokens. Some third-party sites say more.
-
License
It is listed under Mistral's commercial license, not as open weight.
-
Code privacy
Check data terms before sending private code.
-
Your languages
Test with your own languages and frameworks.
Alternatives
Models to compare it with
Qwen3-Coder
Qwen's open-weight coding models under Apache 2.0, from the efficient Qwen3-Coder-Next to the large 480B model, with tool use and long context.
Mistral Medium 3.5
A newer open-weight Mistral model for agent and coding work, with image input, tool calling, structured outputs and a 256K window.
Claude Opus 5.5
Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
Keep exploring
Solutions, services and guides
Related services
View all related servicesSolutions
View all solutions- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
- Automated quoting Draft accurate quotes and proposals from a request, your price rules and past work, for a person to approve.
- AI-assisted content workflows Briefs, first drafts, edits and repurposing in a workflow where people set the angle and approve every word.
- Payroll automation Turn pay rules, attendance and leave into tested software so the monthly run becomes a review and payslips go out in one batch.
- Contract review assistant Highlight unusual clauses, missing terms and deviations from your standard positions, so reviewers focus where it matters.
- Screening assistant Summarize each application against your criteria, flag strong matches and missing information, and leave every decision to a person.
Industries
View all industries- Professional services Client portals, proposal drafting, knowledge assistants and internal tools for consultancies, agencies and firms.
- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Education and elearning Course platforms, student portals, content workflows and AI tutoring assistants for schools and training companies.
Guides and articles
View all guides and articlesMCP servers
View all mcp servers- Context7 Upstash's Context7 MCP server gives coding assistants current, version-specific documentation for thousands of libraries.
- Git The MCP project's Git reference server lets AI read history and diffs and stage, commit and switch branches in a local repository.
- GitHub GitHub's official MCP server lets AI read repositories, search code, manage issues and pull requests and, when allowed, change files.
- GitLab GitLab's built-in MCP server lets AI read projects, code, merge requests and pipelines and create commits and work items. In beta.
- Sentry Sentry's official MCP server lets AI search errors, events and traces, read issue details, get AI analysis and update issues.
- Sequential Thinking The MCP project's Sequential Thinking reference server gives AI a structured way to break a problem into steps and revise them.
Glossary terms
View all glossary terms- AI copilot An AI copilot is an assistant built into a tool people already use, which suggests, drafts and explains while the person stays in control.
- Large language model A large language model, or LLM, is an AI model trained on vast amounts of text that can understand and generate language, and often images and code.
- Claude Code Claude Code is Anthropic's agentic coding tool, which works in a developer's terminal, IDE, desktop app or browser to read code, run commands and make changes.
- Chatbot A chatbot is software that holds a conversation with people through text or voice, answering questions or completing simple tasks.
- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- Prompt A prompt is the instruction and context you give an AI model to get the output you want.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
The model completes code between existing lines, using what comes before and after, which suits editor completion.
The official Mistral card lists 128K tokens.
No. It is listed under Mistral's commercial license and used through the API.