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MiniMax-M3MiniMax M2.7 Add a modelChat with these 2

AttributeHide identical rows	MiniMax-M3minimax/minimax-m3	MiniMax M2.7minimax/minimax-m2.7
Specs
Context window	1M	205K
Max output	512K	131K
Input modalities	TextImageVideo	Text
Output modalities	Text	Text
Capabilities
Streaming	Supported	Supported
Tool calling	Supported	Supported
Structured output (JSON)	Supported	Supported
Image input	Supported	Not supported
Thinking mode	Supported	Supported
Price / 1M tokens
Input	$ 0.33>= 512K$ 0.66	$ 0.33
Output	$ 1.32>= 512K$ 2.63	$ 1.32
Cache read	$ 0.066>= 512K$ 0.13	$ 0.066
Cache write	$ 0.33>= 512K$ 0.66	$ 0.42
What it is good at
Best for	Multimodal agents Computer use and cowork Long-context research	Complex agent workflows Repository-scale coding
Published benchmarks
Terminal-Bench 2.0pass_rate	—	57%(setup not fully disclosed)
Terminal-Bench 2.1pass_rate	66%Terminus 2(setup not fully disclosed)	—
Multi-SWE-Benchresolved_rate	—	52.7%(setup not fully disclosed)
SWE-Bench Proresolved_ratesetups differ by: harness	59%Claude Code(setup not fully disclosed)	56.22%(setup not fully disclosed)
SWE-Bench Verifiedresolved_rate	80.5%(setup not fully disclosed)	—
GDPval-AAelo	—	1495(setup not fully disclosed)
MMMU Pro (no tools)accuracy	78.1%(setup not fully disclosed)	—
MCP Atlas Publicscore	74.2%(setup not fully disclosed)	—
Toolathlonscore	—	46.3%(setup not fully disclosed)