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Reasoning · Mistral AI

Run Magistral Small in the EU through an OpenAI-compatible API

Magistral Small is the open reasoning model from Paris-based Mistral AI: a 24-billion-parameter model that thinks through a problem before it answers, and since version 1.2 also reads images. On inference.eu you call it with the OpenAI or Anthropic request format, processed in EU data centres and never used for training.

Contact salesExample request
  1. 0124B
  2. 02EU data centres
  3. 03Apache 2.0

What Magistral Small is

Magistral Small 1.2, published as Magistral-Small-2509 in September 2025, is built on Mistral Small 3.2 and trained further for reasoning, first with supervised fine-tuning on traces from the larger Magistral Medium and then with reinforcement learning. It is a dense model with 24 billion parameters.

Before answering, the model writes out its reasoning between dedicated thinking tags, then gives a final answer. Version 1.2 adds a vision encoder, so it can reason about images as well as text. The context window is 128K tokens, although Mistral notes that performance may degrade beyond about 40K. The weights are released under Apache 2.0.

What it does well, and where it falls short

Magistral Small is good at problems that benefit from step-by-step thinking: maths, logic, planning, checking calculations and explaining a decision. Its reasoning trace is readable, which helps when you need to show how an answer was reached. It supports dozens of languages, including French, German, Italian, Spanish, Polish and Portuguese, and its size keeps it relatively light to serve.

Thinking costs tokens and time, so it is the wrong choice for simple chat or extraction. Very long inputs are a weak spot, given the drop-off past roughly 40K tokens. Mistral Small 4 now combines reasoning, vision and coding in one larger model, and is often the better default for new projects.

Calling Magistral Small through the API

inference.eu uses the OpenAI request format, so the OpenAI SDKs, LangChain, LlamaIndex and other compatible tools work unchanged. Set the base URL to the inference.eu API, use your inference.eu key and set the model to magistral-small.

Mistral recommends using the model's default system prompt, which tells it to think before answering, and sampling with temperature 0.7 and top_p 0.95. Leave enough room in max_tokens for the reasoning trace as well as the answer. Images go in as image_url content parts. The Anthropic Messages format is also available for tools built around Claude.

A French reasoning model, processed in the EU

Magistral Small is built by Mistral AI in France, and on inference.eu it runs in the European Union too. Your prompts, images, the model's reasoning trace and its answers are processed in EU data centres, and none of it is used to train any model.

We sign a data processing agreement under Article 28 of the GDPR with every customer and share our subprocessor list. Billing is in euros. The Apache 2.0 licence allows commercial use without user or revenue limits, so you can use the model in paid products, internal tools and customer-facing services without a separate agreement with Mistral.

magistral-small · Python
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.inference.eu/v1", api_key=os.environ["INFERENCE_EU_API_KEY"])

response = client.chat.completions.create(
    model="magistral-small",
    messages=[{"role": "user", "content": "Summarise this contract in five bullet points."}],
)
print(response.choices[0].message.content)

What teams use it for

  • 1

    Calculation and plan checking

    Check quotes, schedules and calculations step by step and point out where a figure or assumption does not add up.

  • 2

    Explainable decisions

    Produce a written line of reasoning alongside an answer, for reviewers who need to see why a recommendation was made.

  • 3

    Maths and STEM tutoring

    Work through exercises in maths, physics or engineering, including problems given as a photo or diagram.

Magistral Small 1.2: common questions

The questions buyers, developers and legal teams ask us most. Something missing? Ask us directly.

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