MiniMax Unveils M3 AI Model for Coding and Automation
Quick Look
- Chinese AI startup MiniMax launched its M3 model, boasting reduced computational needs, faster speeds, and a 1 million token processing capacity.
- It reportedly outperforms rivals like GPT-5.5 and Gemini 3.1 Pro on coding benchmarks.
AI-generated summary
Why It Matters
Chinese artificial intelligence start-up MiniMax has unveiled its latest flagship AI model, M3, designed to anchor the company’s push into coding agents and automated workflows. The model's redesigned architecture reduced computational requirements to as little as one-twentieth of previous levels, slashing inference costs while boosting response speeds.
Chinese artificial intelligence start-up MiniMax has unveiled its latest flagship AI model, M3, designed to anchor the company’s push into coding agents and automated workflows.
The Shanghai-based company said on Monday that the model’s redesigned architecture reduced computational requirements to as little as one-twentieth of previous levels, slashing inference costs while boosting response speeds.
Notably, MiniMax said M3 could process up to 1 million tokens of data at once – five times more than its predecessor, the M2.7. This allowed the model to handle long, complex programming projects. In one benchmark test cited by the company, M3 successfully figured out how to optimise software running on Nvidia’s Hopper chips.
According to the company’s WeChat post, MiniMax-M3 beat rival models like OpenAI’s GPT-5.5 and Google’s Gemini 3.1 Pro on the major coding benchmark SWE-Bench Pro, showing that the model was highly capable at handling software engineering and automated tasks.
The company did not disclose the size of the model or the computing infrastructure it used for training.
Open Questions
- What is the exact size of the M3 model?
- What computing infrastructure was used for training M3?
- What are the specific details of the benchmark tests against GPT-5.5 and Gemini 3.1 Pro?
- What are the specific applications MiniMax envisions for M3 beyond coding agents and automated workflows?
