Mistral: Mistral Medium 3.1

Public pricingIntelligence 79/100Medium memoryविज़नटूल उपयोग

Mistral: Mistral Medium 3.1 एक मल्टीमॉडल मॉडल है, जिसे vision-language समझ के लिए बनाया गया है। यह multimodal input handling، छवि समझ, 131K tokens का context और संतुलित लागत profile जोड़कर vision-language understanding and content analysis में भरोसेमंद काम करता है। यह तब व्यावहारिक विकल्प है जब गुणवत्ता, गति और लागत महत्वपूर्ण हो, खासकर उन टीमों के लिए जिन्हें स्थिर output,

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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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.

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