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Mistral Large 2407

mistralai/mistral-large-2407

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This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement here(opens in new tab).

It supports dozens of languages including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, along with 80+ coding languages including Python, Java, C, C++, JavaScript, and Bash. Its long context window allows precise information recall from large documents.

Modalities

Input Price

$2per 1M

Output Price

$6per 1M

Context

131K

Weekly Tokens

272M

Released

Nov 19, 2024

Overview
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API

Sample code and API for Mistral Large 2407

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use mistralai/mistral-large-2407 with the OpenRouter API:

OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

Endpoint

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelmistralai/mistral-large-2407

Parameters

NameTypeDefaultDescription
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penaltyfloat0Adjusts how often the model repeats specific tokens already used in the input.
seedinteger—If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
response_formatmap—Forces the model to produce specific output format.
toolsarray—Tool calling parameter, following OpenAI's tool calling request shape.
tool_choicestring or object—Controls which (if any) tool is called by the model.