Model comparison
MiniMax M2.7 vs Gemini 2.5 Pro
Capability radar, value bars, and side-by-side posture.
MiniMax M2.7
Not scored
value score
Gemini 2.5 Pro
93
value score
MiniMax M2.7 ctx
—
Gemini 2.5 Pro ctx
1.0M
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- Gemini 2.5 Pro93
Attribute tape
| Field | MiniMax M2.7 | Gemini 2.5 Pro |
|---|---|---|
| Developer | minimax | Google DeepMind |
| Context | — | 1.0M |
| Modalities | Text, Code, Image, Audio, Video | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $1.25/1M in · $10/1M out |
| Value score | — | 93 |
| Summary | MiniMax M2.7 is a sparse Mixture-of-Experts (MoE) reasoning language model developed by MiniMax, designed for agentic coding, tool use, and multi-step workflow automation. It is positioned for software engineering, document generation, and productivity tasks, with a training process that incorporated self-improvement techniques where the model helped optimize parts of its own development pipeline. | Google frontier multimodal model. |