Model comparison
MiniMax M2.7 vs GPT-5
Capability radar, value bars, and side-by-side posture.
MiniMax M2.7
Not scored
value score
GPT-5
94
value score
MiniMax M2.7 ctx
—
GPT-5 ctx
400K
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- GPT-594
Attribute tape
| Field | MiniMax M2.7 | GPT-5 |
|---|---|---|
| Developer | minimax | OpenAI |
| Context | — | 400K |
| Modalities | Text, Code, Image, Audio | |
| Openness | — | Proprietary Model |
| Speed | — | Fast |
| Price | — | Mid-High |
| Value score | — | 94 |
| 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. | OpenAI frontier multimodal model. |