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Mistral · Open weights

Mistral Small 4 119B

Added Mar 16, 2026Open weights

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Use in the app

Mistral Small 4 is a hybrid MoE model that unifies instruct, reasoning, and coding behavior in a single multimodal model. It supports text and image input, native function calling, JSON output, and per-request reasoning effort controls.

  • Reasoning
  • Tools
  • Vision
  • Structured output
Input
Text, Images
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.40
Output
$1.40

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
16.4K
Average output (7 days)
92 tokens
Longer than 9% of 468 models

Side by side

Mistral Small 4 119B compared

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

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Mistral Small 4 119BMistralThis modelGPT OSS 20BOpenAIRemove
ProviderMistralOpenAI
Discovery tierOpen weightsOpen weights
AddedMar 16, 2026Aug 5, 2025
Limits
Context window262.14KBest131.07K
Max output16.38K16.38K
Average output92 tokens1.9K tokens
Pricing, USD per 1M tokens
Input$0.40$0.02Best
Output$1.40$0.10Best
Performance
Throughput128.8 tok/s—
Time to first token0.7 s—
Request success (24h)99.6%99.6%
Benchmark indexes
Intelligence Index9.09.0
Coding Index—20.7
Math Index—89.3
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesNo
Structured outputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • Mistral Small 4 119B
  • GPT OSS 20B

Intelligence Index

  • Mistral Small 4 119B9.0
  • GPT OSS 20B9.0

Mistral Small 4 119B: Better than 16% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 20.7

  • Math Index

    Composite of the math evaluations

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 89.3

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 0.2%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 0.0%

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 339 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 2.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Mistral Small 4 119B: 28.3%
    • GPT OSS 20B: 34.7%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 1.1%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Mistral Small 4 119B: 3.8%
    • GPT OSS 20B: 11.0%Top

  • GPQA Diamond

    Graduate-level science questions

    • Mistral Small 4 119B: 57.1%
    • GPT OSS 20B: 68.8%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 74.8%

  • IFBench

    Following precise output instructions

    • Mistral Small 4 119B: 32.8%
    • GPT OSS 20B: 65.1%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 0.0%

  • SciCode

    Scientific computing in Python

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 38.9%

  • LiveCodeBench

    Recent competitive programming problems

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 77.7%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Mistral Small 4 119B: —
    • GPT OSS 20B: 89.3%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Mistral Small 4 119B: 10.6%Top
    • GPT OSS 20B: 10.6%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Mistral Small 4 119B: 18.4%
    • GPT OSS 20B: 60.2%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Mistral Small 4 119B: 28.3%
    • GPT OSS 20B: 34.7%Top

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.

Throughput
128.8 tok/s
Faster than 70% of 254 models
Time to first token
0.7 s
Quicker than 99% of 254 models
Prompt cache hits
16.9%
Request success (24h)
99.6%
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 95.4%
  • 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-small-4-119b-2603",
    "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-4-119b-2603",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Mistral

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