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MiniMax Latest

Compatibility alias for MiniMax M3 Thinking, retaining its existing request format and structured-output support. The newer MiniMax M3.1 Flash is available separately as minimax/minimax-m3.1-flash and has different request parameter support.

  • Reasoning
  • Vision
  • Tool Calling
  • Structured Output

Added May 3, 2026

Pricing

Auto routing · per 1M tokens
Input
$0.23
Output
$0.96
Cache read
$0.050

Specifications

Context window
512K
Max output
80K

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

29.2

Better than 83% of models compared

Coding Index

58.6

Better than 69% of models compared

Agentic Index

29.5

Better than 71% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

21.3%

Better than 41% of models compared

AutomationBench-AA Tasks Completed

Fully completed workflows without guardrail violations

4.4%

Better than 44% of models compared

Harvey LAB-AA v1.1

Legal tasks fully passed without material hallucinations

0.0%

Better than 9% of models compared

AA-Briefcase v1.1

Agentic knowledge work (Elo)

1090 Elo

Better than 54% of models compared

GDPval-AA v2.1

Economically valuable tasks (Elo)

1242 Elo

Better than 62% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

9.8%

Better than 40% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

83.0%

Better than 95% of models compared

MLCR-AA

Medical long-context reasoning

4.4%

Better than 10% of models compared

Reasoning

HLE

Humanity's Last Exam

39.0%

Better than 86% of models compared

IFBench

Instruction-following benchmark

82.9%

Better than 99% of models compared

CritPt

Research-level physics reasoning

3.7%

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

2.0%

Better than 47% of models compared

SciCode

Python programming for scientific computing

47.1%

Better than 42% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

16.7%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

18.4%

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

92.9%

Better than 96% of models compared

Terminal-Bench Hard (legacy)

Agentic coding and terminal use

42.4%

Better than 89% of models compared

T²-Bench Telecom (legacy)

Conversational AI agents in dual-control scenarios

88.9%

Better than 83% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

83.0%

Better than 95% of models compared

GDPval-AA (unversioned / legacy)

Economically valuable tasks

37.1%

Last updated Oct 22, 2026

Artificial Analysis

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