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  4. MiniMax M2.7
MiniMax
Released March 18, 2026

MiniMax M2.7

MiniMax M2.7 from MiniMax is built for complex agent teams, self-evolution, software engineering, and office editing with strong tool use.

Visit MiniMaxAnnouncement
Inputs
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Outputs
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Model Overview

Capabilities, design details, and architectural traits

MiniMax M2.7 - self-evolving agent model

MiniMax M2.7 is built around self-improvement and complex agent workflows. It is presented as a model for software engineering, office tasks, and multi-agent coordination.

TraitDocumented detail
Self-improvement loopIt is described as a model that participated in its own evolution and uses repeated optimization cycles.
Agent TeamsIt is built to work with multiple agents and to handle complex agent harnesses.
Tool useIt supports tool interaction and dynamic tool search during task execution.
Office editingIt is documented for multi-turn, high-fidelity editing in Excel, PowerPoint, and Word.
Coding and engineeringIt is highlighted for end-to-end software delivery, bug hunting, security analysis, and ML tasks.

Agent workflow

The model is framed as a system for handling hard, multi-step productivity work. Its identity is tied to repeated refinement, tool use, and coordinated execution across agent roles.

Workspace focus

It is also positioned for professional office work, with stronger handling of complex edits and document workflows. The model page emphasizes productivity tasks rather than general chat alone.

Benchmark Performance

Independent evaluations · Artificial Analysis

38.9%
Intelligence
52.6%
Coding Index
25.9%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science87.4%
Humanity's Last Exam29.6%
SciCode - Scientific Coding47.0%
Instruction Following75.7%
Long Context Reasoning75.3%
τ²-Bench - Agentic Tasks84.8%
TerminalBench - System Control39.4%
Specs
Context window
205Ktokens
Input pricing
$0.30per 1M tokens
Output pricing
$1.20per 1M tokens
Cached input
$0.06per 1M tokens

Prices in USD.

Key Capabilities & Ratings

Coding60%
Tool Calling / API50%
Coding & Dev40%
Legal & E-Discovery1.5k
Index Score
Financial Analysis1.5k
Index Score

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderMiniMaxAnthropicAnthropic
Release DateMarch 18, 2026July 24, 2026June 9, 2026
Knowledge Cutoff-May 2026-
Context & Limits
Context Window205K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.30
Best Input Pricing
$5$10
Output Pricing
$1.20
Best Output Pricing
$25$50
Modalities
Inputs
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Outputs
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Benchmarks (0-100)
Intelligence Index38.9
63.1
Best Intelligence Index
62.1
Coding Index52.6
78.0
Best Coding Index
76.5
Agentic Index25.9
59.2
Best Agentic Index
56.6
MiniMax M2.7
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

87%
MiniMax M2.7
GPQA Benchmark
Score: 87%
MiniMax M2.7
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

30%
MiniMax M2.7
Humanity's Last Exam
Score: 30%
MiniMax M2.7
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

75%
MiniMax M2.7
Long Context Reasoning
Score: 75%
MiniMax M2.7
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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