Mistral

Mistral Medium 3.1 — Benchmark Scores, Pricing & Performance Analysis

Chatbot Arena ELO
1250
Output Speed
110 tok/s
Input Cost
$0.40/1M
Output Cost
$2.0/1M
Context Window
131K
Max Output
105K
Knowledge Cutoff
Jun 2025
Accepts
text, image, file

Mistral Medium 3.1 by Mistral demonstrates competitive pricing. View detailed benchmark data including scores across coding, math, reasoning, speed, and cost metrics.

Specifications last checked against the provider on . Benchmark scores carry their own source, linked beside each number.

General Benchmarks

MMLU-Pro
66.0%53rd of 66

Massive Multitask Language Understanding professional benchmark

HuggingFace Leaderboard
Chatbot Arena ELO
125054th of 74

Human preference ELO from blind head-to-head votes

LMSYS / HuggingFace

Coding Benchmarks

Website Arena ELO
114572nd of 108

Human preference ELO for building a working web page from a brief

Design Arena (via OpenRouter)
AA Coding Index
20.576th of 96

Artificial Analysis composite coding score

Artificial Analysis (via OpenRouter)
LiveCodeBench
34.0%51st of 66

Live competitive programming benchmark

livecodebench.github.io
HumanEval+
77.0%54th of 66

Code generation correctness with extended tests

Papers
SWE-bench Verified
28.0%51st of 67

Real-world software engineering task resolution

swebench.com
Design Arena ELO
109987th of 120

Human preference ELO for building things — websites, UI, games, charts, SVG

Design Arena (via OpenRouter)

Math Benchmarks

GSM8K
86.0%54th of 66

Grade school math word problems

Papers
MATH
68.0%52nd of 66

Competition mathematics problem solving

Papers

Reasoning Benchmarks

ARC-AGI
18.0%44th of 66

Abstraction and Reasoning Corpus for general intelligence

arcprize.org
GPQA Diamond
40.0%126th of 140

Graduate-level science Q&A by domain experts

Papers
AA Agentic Index
3.156th of 70

Artificial Analysis composite score for multi-step tool-using tasks

Artificial Analysis (via OpenRouter)

Speed Benchmarks

Time to First Token
200 ms15th of 92

Latency before first token arrives

Aggregated
Output Speed
110 tok/s29th of 94

Tokens generated per second

Aggregated

Cost Benchmarks

Output Cost
$2.0244th of 413

Cost per 1M output tokens

OpenRouter API
Cached Input Cost
$0.0439th of 136

Cost per 1M cached input tokens — the price that actually applies to a long agent conversation

OpenRouter API
Input Cost
$0.40227th of 413

Cost per 1M input tokens

OpenRouter API

Context Benchmarks

Context Length
131K212th of 451

Maximum context window size

OpenRouter API

Available from 4 providers

The same model costs different amounts depending on who serves it. You can bring your own key for 3 of these — connect it here.

ProviderInput / 1MOutput / 1MCached inContextYour key
Mistral$0.4$2—262KSupported
NanoGPT$0.4$2$0.2131K—
OpenRouter$0.4$2$0.04131KSupported
Vercel AI Gateway$0.4$2—128KSupported

Mistral Medium 3.1 — Benchmark Scores Overview

Scores normalized to percentage scale for visual comparison. ELO scores mapped to 0-100 range (1100-1500).

Mistral Medium 3.1 — Frequently Asked Questions

How intelligent is Mistral Medium 3.1?

Mistral Medium 3.1 scores 1250 on the Chatbot Arena ELO rating, making it a mid-tier AI model. This score is based on blind head-to-head human preference voting.

How much does Mistral Medium 3.1 cost?

Mistral Medium 3.1 costs $0.40 per 1M input tokens and $2.0 per 1M output tokens. This makes it one of the more affordable models.

How fast is Mistral Medium 3.1?

Mistral Medium 3.1 generates output at 110 tokens per second, which is moderate compared to other models. The time to first token is 200 ms.

How good is Mistral Medium 3.1 at coding?

Mistral Medium 3.1 achieves 28.0% on SWE-bench Verified, demonstrating basic real-world software engineering capability. This benchmark tests the model's ability to resolve actual GitHub issues.

How good is Mistral Medium 3.1 at math and reasoning?

Mistral Medium 3.1 scores 68.0% on the MATH benchmark (competition-level mathematics). It also achieves 40.0% on GPQA Diamond, a graduate-level science reasoning benchmark.

What is the context window of Mistral Medium 3.1?

Mistral Medium 3.1 has a context window of 131K tokens. This determines how much text, conversation history, and code the model can process in a single request.

Who created Mistral Medium 3.1?

Mistral Medium 3.1 was created by Mistral. It is classified as a mid model in our catalogue.

Is Mistral Medium 3.1 open source?

No, Mistral Medium 3.1 is a proprietary model. It is available through Mistral's API and compatible providers.