Code Generation
Generates code from natural language instructions or partial code inputs across 80+ programming languages, including Python, Java, C++, and Bash.
Mistral
Mistral Codestral
Mistral Codestral is an open-weight generative AI model built by Mistral and designed specifically for code generation tasks. It operates through a shared instruction and completion API endpoint, allowing developers to both write new code and interact with existing codebases. The model is trained on a dataset spanning more than 80 programming languages, including Python, Java, C, C++, JavaScript, Bash, Swift, and Fortran. Codestral is intended for developers building AI-assisted coding tools and applications, as it handles both code and English fluently. Its broad language coverage makes it applicable across a wide range of development environments and project types. Because it is open-weight, it can be deployed and integrated in ways that closed models typically do not permit.
Unknown
32,000 context
16,000 tokens output
Code Generation
Code Completion
Instruction Following
Long Context Handling
Multi-language Support
API Integration
Model Overview
High-signal model metadata in a structured two-column overview table.
Provider
The entity that provides this model.
Mistral
Input Context Window
The number of tokens supported by the input context window.
32,000
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
16,000 tokens
tokens
Open Source
Whether the model's code is available for public use.
No
Release Date
When the model was first released.
Unknown
Knowledge Cut-off Date
When the model's knowledge was last updated.
Unknown
API Providers
The providers that offer this model. This is not an exhaustive list.
Mistral API, Hugging Face
Modalities
Types of data this model can process.
Text
Code
What is Mistral Codestral
A fuller summary of positioning, capabilities, and source-specific details for Mistral Codestral.
Mistral Codestral is an open-weight generative AI model built by Mistral and designed specifically for code generation tasks. It operates through a shared instruction and completion API endpoint, allowing developers to both write new code and interact with existing codebases. The model is trained on a dataset spanning more than 80 programming languages, including Python, Java, C, C++, JavaScript, Bash, Swift, and Fortran.
Codestral is intended for developers building AI-assisted coding tools and applications, as it handles both code and English fluently. Its broad language coverage makes it applicable across a wide range of development environments and project types. Because it is open-weight, it can be deployed and integrated in ways that closed models typically do not permit.
Capabilities
What Mistral Codestral supports
Code Completion
Fills in incomplete code snippets using a shared completion API endpoint, supporting mid-file and end-of-file completion patterns.
Instruction Following
Responds to natural language coding instructions through a shared instruction endpoint, enabling conversational code editing and generation.
Long Context Handling
Supports a 32,000-token context window, allowing it to process and generate code across large files or multi-function codebases in a single pass.
Multi-language Support
Trained on over 80 programming languages, including both widely used languages like JavaScript and more specialized ones like Fortran and Swift.
API Integration
Accessible via Mistral's API using a unified endpoint that handles both instruction and completion request formats for flexible integration.
Pricing for Mistral Codestral
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Input tokens
$0.20
Per million tokens
Output tokens
N/A
Per million tokens
Price Comparison
Additional usage-cost dimensions synced into the project for this model.
maxTemperature
1
maxResponseSize
16,000 tokens
API Access & Providers
Places where this model is available, based on the synced detail-page metadata.
Mistral API
Hugging Face
Resources & Documentation
Official model cards, release notes, docs, and other references synced from the source page.
Community discussion
What people think about Mistral Codestral
Mistral Codestral discussions are most active in r/CLine, r/mcp, r/AISEOInsider. Top Reddit threads cluster around coding workflow discussions. The strongest match in this snapshot has 7 upvotes and 6 comments.
It is very good for coding It is better than codellama please add it. Thanks 😊
FAQ
Common questions about Mistral Codestral
What is the context window for Mistral Codestral?
Mistral Codestral supports a context window of 32,000 tokens, which allows it to handle large code files or extended multi-function inputs in a single request.
How many programming languages does Codestral support?
Codestral is trained on a dataset covering more than 80 programming languages, including Python, Java, C, C++, JavaScript, Bash, Swift, and Fortran.
Is Codestral an open-weight model?
Yes, Codestral is an open-weight model released by Mistral, meaning the model weights are made available for download and self-hosted deployment.
What API endpoints does Codestral support?
Codestral uses a shared instruction and completion API endpoint, supporting both instruction-style prompts and fill-in-the-middle code completion requests.
What is the knowledge cutoff date for Codestral?
A specific training cutoff date is not listed in the available metadata for Mistral Codestral.
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