Mistral Small

Mistral chat Free

API ID: mistralai/mistral-small

Input Price
Free
/1M tokens
Output Price
Free
/1M tokens

About Mistral Small

Mistral Small is Mistral AI's efficient model, optimized for high-volume applications requiring fast responses and low costs. Despite its compact size, it delivers impressive performance on general tasks, outperforming many larger models from previous generations. The model excels at straightforward conversation, content generation, summarization, and basic coding tasks. Mistral Small features fast inference times suitable for real-time applications and interactive experiences. It supports function calling and JSON mode for structured outputs. The model is particularly valuable for customer-facing applications, chatbots, and high-throughput processing where cost optimization is critical. Mistral Small offers European data residency options, appealing to organizations with GDPR compliance requirements. For developers seeking capable AI at minimal cost with European provider benefits, Mistral Small provides an excellent entry point to Mistral's ecosystem. It's widely used for initial processing stages and applications where simpler tasks don't justify larger model costs.

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Price Ranking
#1 lowest price among 950 Chat models โ€” Top 20% cheapest!

Model Specifications

Context Length
32k
Max Output
โ€”
Release Date
2024-01-10
Capabilities
chat
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
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This model is completely free!

No token costs - use it without worrying about API bills.

Estimate Token Usage

Mistral Model Lineup

Compare all models from Mistral to find the best fit

Model Input Output Context Capabilities
Mistral Small Current Free Free 32k chat
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๐Ÿš€ Quick Start

Get started with Mistral Small 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-small",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)