MiniMax-M2 is the tool-use specialist of the open-weight field: 230B total parameters with just 10B active, MIT-licensed, and tuned specifically for agentic loops — 69.4% SWE-bench Verified, 46.3 Terminal-Bench, 83 LiveCodeBench. Mid-2026 roundups still rank it the best open model for tool-driven agents.
The 10B active footprint is the strategic choice: agent workloads burn tokens on long multi-step loops, and M2 delivers near-frontier agentic quality at interactive speed and low serving cost. For teams building autonomous agents rather than chat products, M2 is frequently the efficiency-optimal pick.
MiniMax-M2 specifications
| Vendor | MiniMax (China) |
|---|---|
| Architecture | Mixture-of-Experts, agent- and tool-use-optimized |
| Total parameters | 230B |
| Active parameters | 10B |
| Context window | ~200K tokens |
| Modalities | text |
| License | MIT — weights free to download, self-host, fine-tune, and use commercially |
| Release date | 2025-10-27 |
| Weights | Hugging Face · GitHub |
Benchmarks and reported results
| Benchmark | Result | Note |
|---|---|---|
| SWE-bench Verified | 69.4% | |
| Terminal-Bench | 46.3 | |
| LiveCodeBench | 83 |
Running MiniMax-M2 locally
230B total but only 10B active: 4-bit builds run around 130GB, and the tiny active footprint makes it unusually fast per token. One of the best capability-per-dollar self-host targets for agent backends.
What MiniMax-M2 is best for
- Tool-calling agents and terminal/computer-use workloads
- High-throughput agent loops where per-token cost compounds
- Self-hosting on a modest multi-GPU node (MIT license)
Frequently asked questions
What makes MiniMax-M2 good for agents specifically?
It was optimized for multi-step tool use rather than single-shot chat: strong Terminal-Bench (46.3) and SWE-bench Verified (69.4%) scores with only 10B active parameters, so long agentic loops stay fast and cheap.
Can I self-host MiniMax-M2?
Yes — MIT license, ~130GB at 4-bit for the 230B weights. A 2×80GB node or high-memory workstation handles it, with vLLM and SGLang support.