# MiniMax publishes M3.1-Flash weights: a 428B multimodal MoE with a 1M-token context and a 252 GB download

> OnPrem World · https://onpremworld.com/en/news/2026-10-minimax-m3-1-flash-open-weights · CC BY 4.0

Published: 2026-10-23 · Models

MiniMax released the open weights of MiniMax-M3.1-Flash on Hugging Face on October 23. It is a native multimodal mixture-of-experts model with about 428B total parameters and 23B active per token, taking text, image and video input with a context window of up to 1M tokens, and it is aimed at coding, agent workflows, computer use and cybersecurity. Compared with MiniMax-M3 it uses sparse attention in every layer, quantization-aware training and a new DSpark speculative-decoding draft head, which ships with the weights. MiniMax recommends SGLang, vLLM or TokenSpeed to serve it, and the weights come under the MiniMax Community License rather than an open-source license.

## Why it matters locally

It is another open-weight agent model in the same class as DeepSeek V4.1 Flash, but its license asks commercial users to show a "Built with MiniMax M3.1-Flash" credit and send MiniMax a one-time notice, or get prior written approval above US$20 million in yearly revenue.

## For the market

MiniMax's own table puts M3.1-Flash level with Opus 5 on BankerToolBench (76.2) but behind DeepSeek V4.1 Flash-1017 on Terminal Bench 4.0 (38.1 versus 42.3), so the two Chinese labs look closely matched on agent work. The deciding factor for many companies will likely be the license: DeepSeek's MIT terms are simpler than MiniMax's notice-and-approval rules.

## In plain words

MiniMax, a Chinese AI company, has made one of its big AI models free to download, and it can read text, pictures and videos and work through long multi-step jobs. The files add up to about 252 GB, so it needs a very large computer, and businesses that use it to make money have to tell MiniMax first.

## For practitioners

The Hugging Face repo totals about 252 GB, so plan for more than 256 GB of memory once the KV cache for long contexts is added: an M5 Ultra Mac Studio in the 512 GB configuration Apple has announced, or a multi-GPU server, is the realistic starting point. Use SGLang, vLLM or TokenSpeed as MiniMax recommends (Transformers, KTransformers and unsloth support are still in progress), start from temperature 1.0 and top_p 0.95, and test whether the DSpark draft head speeds up your own workload.

## Source

[MiniMax-M3.1-Flash model card (Hugging Face)](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash)

## On this site

- Models: [DeepSeek-V4-Flash](https://onpremworld.com/en/models/deepseek-v4-flash.md)
- Hardware: [M5 Ultra](https://onpremworld.com/en/hardware/apple-m5-ultra.md)
- Hardware: [RTX PRO 6000 Blackwell Workstation Edition](https://onpremworld.com/en/hardware/nvidia-rtx-pro-6000-blackwell.md)

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