Mistral Small 4 119B

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
  • Vision
  • Tool Calling
  • Structured Output

Added Mar 16, 2026

Model weights

Pricing

Auto routing · per 1M tokens
Input
$0.40
Output
$1.40
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Specifications

Context window
262.1K
Max output
16.4K
Parameters
119B / 6B
Total / active
Avg output (7d)
185 tokens
Longer than 13% of models

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

9.0

Better than 35% of models compared

Agentic work

T²-Bench Telecom (legacy)

Legacy fallback · Conversational AI agents in dual-control scenarios

18.4%

Better than 16% of models compared

Document reasoning

AA-LCR v1.1

Long context reasoning with updated grading

28.3%

Better than 29% of models compared

Reasoning

HLE

Humanity's Last Exam

3.8%

Better than 10% of models compared

IFBench

Instruction-following benchmark

32.8%

Better than 21% of models compared

CritPt

Research-level physics reasoning

0.3%

Coding

Terminal-Bench Hard (legacy)

Legacy fallback · Agentic coding and terminal use

10.6%

Better than 45% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

16.6%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

78.0%

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

57.1%

Better than 31% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

28.3%

Better than 29% of models compared

Last updated Oct 3, 2026

Artificial Analysis

Providers

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