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 weightsPricing
Auto routing · per 1M tokens- Input
- $0.40
- Output
- $1.40
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
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
9.0
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 AnalysisProviders
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