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Mistral · Balanced

Mistral Large 2411

Added Jan 1, 2024

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Use in the app

Upgrade to Mistral's flagship model. It is fluent in English, French, Spanish, German, and Italian, with high grammatical accuracy, with a long context window.

Input
Text
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$2.01
Output
$6.00
Cache read
$0.20

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
102.4K
Average output (7 days)
955 tokens
Longer than 69% of 468 models

Side by side

Mistral Large 2411 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Mistral Large 2411MistralThis modelMistral Code Agent LatestMistralRemove
ProviderMistralMistral
Discovery tierBalancedOpen weights
AddedJan 1, 2024Jun 2, 2026
Limits
Context window128K262.14KBest
Max output102.4KBest32.77K
Average output955 tokens316 tokens
Pricing, USD per 1M tokens
Input$2.01$0.40Best
Output$6.00$2.00Best
Cache read$0.20—
Performance
Request success (24h)100.0%100.0%
Benchmark indexes
Intelligence Index5.88.6Best
Coding Index—31.3
Math Index—36.7
Capabilities
ToolsNoYes
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Mistral Large 2411
  • Mistral Code Agent Latest

Intelligence Index

  • Mistral Large 24115.8
  • Mistral Code Agent Latest8.6

Mistral Large 2411: Better than 3% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 31.3

  • Math Index

    Composite of the math evaluations

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 36.7

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 3.1%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 0.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 482 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 544 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 2.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 32.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Mistral Large 2411: 3.5%
    • Mistral Code Agent Latest: 3.6%Top

  • GPQA Diamond

    Graduate-level science questions

    • Mistral Large 2411: 35.1%
    • Mistral Code Agent Latest: 59.4%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Mistral Large 2411: 51.5%
    • Mistral Code Agent Latest: 76.2%Top

  • IFBench

    Following precise output instructions

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 38.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 0.0%

  • SciCode

    Scientific computing in Python

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 32.8%

  • LiveCodeBench

    Recent competitive programming problems

    • Mistral Large 2411: 17.8%
    • Mistral Code Agent Latest: 44.8%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 36.7%

  • AIME

    Competition mathematics

    • Mistral Large 2411: 0.0%
    • Mistral Code Agent Latest: —

  • MATH-500

    Competition math problems

    • Mistral Large 2411: 52.7%
    • Mistral Code Agent Latest: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 18.9%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 24.9%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Mistral Large 2411: —
    • Mistral Code Agent Latest: 32.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
81.6%
About $0.53 per 1M input tokens with caching
Request success (24h)
100.0%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 100.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/mistral-large",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="mistralai/mistral-large",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Mistral

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