Mistral Large

Mistral chattool_use

API ID: mistralai/mistral-large

Input Price
$2.00
/1M tokens
Output Price
$6.00
/1M tokens
Cached Input
$0.20
Save 90%

About Mistral Large

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](https://mistral.ai/news/mistral-large-2407/). 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.

๐Ÿ’ฐ
Price Ranking
#1097 lowest price among 1240 Chat models

Model Specifications

Context Length
128k
Max Output
โ€”
Release Date
2024-02-26
Capabilities
chat tool_use
Input Modalities
textfile
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$2.70
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$84.00
/month
1000 tickets/day, ~800 tokens each

Mistral Model Lineup

Compare all models from Mistral to find the best fit

Model Input Output Context Capabilities
Mistral Large Current Free Free 128k chat tool_use
Pixtral 12B Free Free 4k chat vision
Mistral 7B Instruct v0.3 Free Free 33k chat
Mistral 7B Instruct Free Free 33k chat
Mixtral 8x22B (base) Free Free 66k chat
Mixtral 8x22B (base) Free Free 66k chat

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Meta Llama 3.1 405B Instruct
Input: $4.00
Output: $4.00
Context: 131k
Alibaba Qwen Qwen3.8 Max
Input: $2.00
Output: $6.00
Context: 1.0M

๐Ÿš€ Quick Start

Get started with Mistral Large API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="mistralai/mistral-large",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)