Open-weight models

Everything about Magistral Small 1.2

Magistral Small 1.2 in numbers: price per token, context window, independent benchmark scores and comparable models, based on public data checked on October 22, 2026.

Data as of October 22, 2026

Key figures

DeveloperMistral AI
ReleasedSeptember 18, 2025
Context window128,000 tokens (≈ 192 pages)
Maximum output40,000 tokens
Input price$0.50 per million tokens (median of 1 providers)
Output price$1.5 per million tokens
Open weightsYes
Reasoning modeYes
Tool callingYes
Structured output (JSON)Yes
Accepted inputstext, image
Providers offering it1

Overview

Mistral AI released Magistral Small 1.2 on September 18, 2025. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money. Its weights are published: you can download it and run it on your own servers, or use one of the 1 API providers that list it on models.dev. That makes it more than a year old: successors may have shipped since.

We file it under open-weight models (68 models in this category on the site).

How much does Magistral Small 1.2 cost?

Magistral Small 1.2 costs $0.50 per million input tokens and $1.5 per million output tokens (median of 1 providers, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.013; a thousand of those tasks, $13.

That is 1.5 times the median output price of open-weight models ($1).

To estimate your own budget, use the agent cost calculator.

Benchmark results

Epoch AI publishes 2 results for Magistral Small 1.2 on our basket's benchmarks: too few to compute a reliable capability index.

  • GPQA Diamond (PhD-level science questions): 47.6% — the best tracked model, Gemini 4 Argon, reaches 96.4%
  • OTIS Mock AIME (competition mathematics problems): 28.1% — the best tracked model, GPT-5.5 Pro, reaches 100%

What it can do

Its context window reaches 128,000 tokens, roughly 192 pages of text at 500 words per page: enough for a medium-length document. A single answer can run to 40,000 tokens.

It accepts as input: text and image.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

Who is it for?

Given its category, Magistral Small 1.2 is mainly aimed at projects where you want control over your data or hosting, or want to adapt the model to your field.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Alternatives

In the same category, the models closest to Magistral Small 1.2 are:

Independent benchmark scores

BenchmarkWhat it measuresScore
GPQA DiamondPhD-level science questions47.6%
OTIS Mock AIMEcompetition mathematics problems28.1%

Similar models

Other Mistral AI models

Frequently asked questions

How much does Magistral Small 1.2 cost?

As of October 22, 2026, Magistral Small 1.2 costs $0.50 per million input tokens and $1.5 per million output tokens (median of 1 providers). A task that reads 20,000 tokens and writes 2,000 costs about $0.013.

What is the context window of Magistral Small 1.2?

128,000 tokens, roughly 192 pages of text. An answer can reach 40,000 tokens.

Is Magistral Small 1.2 open source?

Its weights are published: you can install it on your own servers. Check the license before commercial use.

When was Magistral Small 1.2 released?

Magistral Small 1.2 was released on September 18, 2025, according to models.dev.

Can you build an agent with Magistral Small 1.2?

Yes: it can call tools and return structured JSON, the two basic building blocks of an agent.

Data sources

Data as of October 22, 2026

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