MiniMax-AI/MiniMax-M2.1

MiniMax M2.1, a SOTA model for real-world dev & agents.

What it solves

MiniMax-M2.1 is an open-source language model designed to make powerful agentic capabilities available to everyone. It tackles the common problem that high-performance AI agents are usually locked behind proprietary services. By releasing the model weights, developers can now build autonomous applications for coding, tool use, instruction following, and long-horizon planning without giving up transparency or control.

How it works

The model is a large language model that has been optimized specifically for agentic tasks. It can be used through the MiniMax API or deployed locally using popular inference frameworks such as SGLang, vLLM, Transformers, MLX-LM, and KTransformers. Recommended inference parameters are provided (temperature=1.0, top_p=0.95, top_k=40) along with a default system prompt. The README also includes a tool calling guide and several deployment guides. The model is evaluated on benchmarks like SWE-bench, Terminal-bench, and the newly introduced VIBE benchmark that verifies full-stack application generation using an Agent-as-a-Verifier approach.

Who it's for

Developers and teams who want to build autonomous coding agents, multi-step workflow automation, or full-stack application generators. It is also useful for researchers and practitioners who need a transparent, locally deployable model with strong agentic and multilingual capabilities.

Highlights

  • Open-source weights under a modified MIT license.
  • Strong performance on software engineering benchmarks, especially multilingual ones, outperforming Claude Sonnet 4.5 and approaching Claude Opus 4.5.
  • Introduction of the VIBE benchmark for evaluating full-stack application development from scratch.
  • Average score of 88.6 on VIBE, with high results in web (91.5) and Android (89.7) subsets.
  • Large gains over the predecessor M2 in tool use (Toolathlon 43.5 vs 16.7) and browser tasks (BrowseComp 47.4 vs 44.0).
  • Works with multiple inference engines and includes deployment guides.
  • Also available via the MiniMax platform API and in the MiniMax Code product.

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