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Mistral · Open weights

Mistral Small 3 24B (2501)

Added Sep 10, 2026Open weights

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Use in the app

Mistral Small 3 24B (2501) hosted by IONOS in Berlin, Germany. Zero data retention.

  • Tools
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.12
Output
$0.35

Reference prices as published by the model provider. API example

Specifications

Context window
32.8K
Max output
8.2K
Average output (7 days)
403 tokens
Longer than 40% of 468 models

Side by side

Mistral Small 3 24B (2501) compared

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

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Mistral Small 3 24B (2501)MistralThis modelGemini 2.5 Flash LiteGoogleRemove
ProviderMistralGoogle
Discovery tierOpen weightsEfficient
AddedSep 10, 2026Jun 17, 2025
Limits
Context window32.77K1.05MBest
Max output8.19K65.54KBest
Average output403 tokens42 tokens
Pricing, USD per 1M tokens
Input$0.12$0.10Best
Output$0.35Best$0.40
Cache read—$0.01
Performance
Throughput—392.8 tok/s
Time to first token—0.6 s
Request success (24h)—99.5%
Benchmark indexes
Intelligence Index6.76.7
Math Index4.335.3Best
Capabilities
ReasoningNoYes
ToolsYesYes
VisionNoYes
Audio inputNoYes
Video inputNoYes
Reasoning effort—low, medium, high

Public evaluations

Benchmarks

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

  • Mistral Small 3 24B (2501)
  • Gemini 2.5 Flash Lite

Intelligence Index

  • Mistral Small 3 24B (2501)6.7
  • Gemini 2.5 Flash Lite6.7

Mistral Small 3 24B (2501): Better than 6% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Mistral Small 3 24B (2501): 4.3
    • Gemini 2.5 Flash Lite: 35.3Top

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Mistral Small 3 24B (2501): 0.0%
    • Gemini 2.5 Flash Lite: 32.0%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Mistral Small 3 24B (2501): 3.8%Top
    • Gemini 2.5 Flash Lite: 3.7%

  • GPQA Diamond

    Graduate-level science questions

    • Mistral Small 3 24B (2501): 46.2%
    • Gemini 2.5 Flash Lite: 47.4%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Mistral Small 3 24B (2501): 65.2%
    • Gemini 2.5 Flash Lite: 72.4%Top

  • IFBench

    Following precise output instructions

    • Mistral Small 3 24B (2501): 26.4%
    • Gemini 2.5 Flash Lite: 31.5%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Mistral Small 3 24B (2501): 25.2%
    • Gemini 2.5 Flash Lite: 40.0%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Mistral Small 3 24B (2501): 4.3%
    • Gemini 2.5 Flash Lite: 35.3%Top

  • AIME

    Competition mathematics

    • Mistral Small 3 24B (2501): 8.0%
    • Gemini 2.5 Flash Lite: 50.0%Top

  • MATH-500

    Competition math problems

    • Mistral Small 3 24B (2501): 71.5%
    • Gemini 2.5 Flash Lite: 92.6%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Mistral Small 3 24B (2501): —
    • Gemini 2.5 Flash Lite: 2.3%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Mistral Small 3 24B (2501): 19.6%Top
    • Gemini 2.5 Flash Lite: 19.0%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Mistral Small 3 24B (2501): 0.0%
    • Gemini 2.5 Flash Lite: 32.0%Top

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

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-small-24b-instruct-2501",
    "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-small-24b-instruct-2501",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Mistral

Other Mistral models, starting with the same family.