Mistral: Mistral Medium 3.1

Public pricingIntelligence 79/100Medium memory비전도구 활용

Mistral: Mistral Medium 3.1은 비전-언어 이해에 맞춘 멀티모달 모델입니다. 멀티모달 입력 처리、이미지 이해, 131K tokens의 컨텍스트, 균형형 비용 특성을 결합해 vision-language understanding and content analysis에서 안정적인 작업을 돕습니다. 특히 품질, 속도, 비용가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

Input

$0.40/1M

Output

$2.00/1M

Cached

$0.04/1M

Batch

$0.20/1M

Calculate your Mistral Medium 3.1 bill.

Set your workload — see cost at your exact volume.

What would Mistral Medium 3.1 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Mistral Medium 3.1 at a glance.

Memory

131,072

tokens

Max reply

4,096

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

mistral

Released

Aug 2025

Training cutoff

Oct 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu

    80

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Mistral Medium 3.1

  • Screenshot analysis, image understanding, or document OCR.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.
  • Multimodal pipelines mixing text + images.

When to look elsewhere

  • Very latency-sensitive, real-time apps where every millisecond counts.

Alternatives

Similar models to compare.

FAQ

Mistral Medium 3.1 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Mistral Medium 3.1 costs roughly $110 per month. Input is $0.40 /1M tokens and output is $2.00 /1M tokens.
Mistral Medium 3.1 has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, Mistral Medium 3.1 supports understanding images, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Mistral Medium 3.1 was released in August 2025, with training data cut off around October 2024.
Models in a similar class include Mistral Medium 3, Mistral Small 3.1 24B, Mistral Large 3 2512. The "Similar models" section below this FAQ links into each.

Still unsure?

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