Model reference · open weights
MiniMax-M2 is an open-weight language model from MiniMaxAI, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Join Our 💬 WeChat 🧩 Discord community. MiniMax Agent ⚡️ API (Now Free for a limited time!) MCP MiniMax Website 🤗 Hugging Face 🐙 GitHub 🤖️ ModelScope 📄 License: MIT Meet MiniMax-M2 Today, we release and open source MiniMax-M2, a Mini model built for Max coding & agentic workflows. MiniMax-M2 redefines efficiency for agents. It's a compact, fast, and cost-effective MoE model (230 billion total parameters with 10 billion active parameters) built for elite performance in coding and agentic tasks, all while maintaining powerful general intelligence. With just 10 billion activated parameters, MiniMax-M2 provides the sophisticated, end-to-end tool use performance expected from today's leading models, but in a streamlined form factor that makes deployment and scaling easier than ever. Highlights Superior Intelligence. According to benchmarks from Artificial Analysis, MiniMax-M2 demonstrates highly competitive general intelligence across mathematics, science, instruction following, coding, and agentic tool use. Its composite score ranks #1 among open-source models globally. Advanced Coding. Engineered for end-to-end developer workflows, MiniMax-M2 excels at multi-file edits, coding-run-fix loops, and test-validated repairs. Strong performance on Terminal-Bench and (Multi-)SWE-Bench–style tasks demonstrates practical effectiveness in terminals, IDEs, and CI across languages. Agent Performance. MiniMax-M2 plans and executes complex, long-horizon toolchains across shell, browser, retrieval, and code runners. In BrowseComp-style evaluations, it consistently locates hard-to-surface sources, maintains evidence traceable, and gracefully recovers from flaky steps. Efficient Design. With 10 billion activated parameters (230 billion in total), MiniMax-M2 delivers lower latency, lower cost, and higher throughput for interactive agents and batched sampling—perfectly aligned with the shift toward highly deployable models that still shine on coding and agentic tasks. Coding & Agentic Benchmarks These comprehensive evaluations test real-world end-to-end coding and agentic tool use: editing real repos, executing commands, browsing the web, and delivering functional solutions. Performanc
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | MiniMaxAI |
|---|---|
| Type | Language models |
| Parameters (lead) | 228.7B |
| Variants | 1 |
| Runs with | transformers |
| Released | 2025-10-22 |
| Popularity | 254k downloads / month |
| Likes | 1,503 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| MiniMax-M2 | 228.7B | BF16 | ~526 GB | — | Weights ↗ |
Using it via the API
Once AxForge deploys minimax-m2 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (minimax-m2 below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"minimax-m2","messages":[{"role":"user","content":"Hello"}]}'
Details
Tags
Papers
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗