Devstral is an agentic LLM for software engineering, developed by Mistral AI and All Hands AI. It’s designed to explore codebases, edit multiple files, and support engineering agents.

Model is trained and ready for deployment

Devstral-Small-2505-unsloth-bnb-4bit

Process an OpenAI-compatible request and send it to the appropriate OpenAI endpoint.

Args:
    msg: JSON string containing the request parameters including 'openai_endpoint'

Returns:
    JSON string containing the response or error

openai_transport

return

Process an OpenAI-compatible request and return a streaming response iterator.
This method is used when stream=True and returns an iterator of strings directly,
without converting to a list or JSON serializing. Supports chat completions and responses endpoints.

Args:
    msg: The request as a JSON string.

Returns:
    Iterator[str]: An iterator yielding text chunks from the streaming response.

openai_stream_transport

prompt

images

audios

videos

chat_history

audio

video

image

tools

tool_choice

The system-level prompt used to define the assistant's behavior.

system_prompt

The maximum number of tokens to generate. Shorter token lengths will provide faster performance.

max_tokens

A decimal number that determines the degree of randomness in the response.

temperature

An alternative to sampling with temperature, where the model considers the results of the tokens with top_p probability mass.

top_p

The level of reasoning effort to apply to the response. Currently supported values are low, medium, and high. 

reasoning_effort

predict

generate

Devstral is an agentic LLM for software engineering, developed by Mistral AI and All Hands AI. It’s designed to explore codebases, edit multiple files, and

Run with API