# MiniMax M1: AI model fact sheet

- **Provider:** minimax
- **Released:** 2025-06-17
- **Context window:** 1,000,000 tokens
- **Parameters:** 456B (45.9B active)
- **API pricing:** $0.30 / 1M input, $1.65 / 1M output
- **OpenRouter ID:** minimax/minimax-m1
- **Capabilities:** conversation, reasoning, code-generation, analysis, agentic-tool-use, memory

MiniMax M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it to process long sequences (up to 1 million tokens) while maintaining competitive FLOP efficiency. With 456 billion total parameters and 45.9B active per token, this variant is optimized for complex, multi-step reasoning tasks.

## Benchmarks

| Benchmark | Score |
| --- | --- |
| FullStackBench | Strong |
| SWE-bench | Competitive |
| MATH | Competitive |
| GPQA | Competitive |
| TAU-Bench | Competitive |

Source: real side-by-side outputs, pricing and specs at https://rival.tips/models/minimax-m1