# MiniMax Debuts M3.1 Flash, a Multimodal MoE Model

> The new release pairs a mixture-of-experts design with agentic, coding, and video-understanding abilities in a single open model.

Published by The Open Weights on Oct 17, 2026. Canonical: https://theopenweights.com/news/minimax-m3-1-flash-ehzr

## Key facts

- Company: MiniMax
- Model: MiniMax-M3.1-Flash
- Version: M3.1-Flash
- Category: Vision-Language
- Modalities: Code, Any-to-Any, Vision-Language
- License: Other (Open weights, commercial use allowed)
- Context window: 1.0M tokens
- Architecture: MiniMaxM3SparseForConditionalGeneration
- Precision: INT8
- Weights size: 224 GB
- Significance: notable
- Published: 2026-10-17
- Last verified: 2026-10-23
- Hugging Face: https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash
- Canonical URL: https://theopenweights.com/news/minimax-m3-1-flash-ehzr

MiniMax has released **MiniMax-M3.1-Flash**, a multimodal model that combines a mixture-of-experts (MoE) architecture with support for vision, code, and general any-to-any tasks. The model is [available on Hugging Face](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash) under a custom license.

According to the release, M3.1 Flash is positioned as a versatile workhorse rather than a narrow specialist. It targets three overlapping use cases that have become the center of gravity for frontier open models:

- **Agentic workflows**, where a model plans and executes multi-step tasks
- **Coding**, a benchmark-heavy area where open models have made rapid gains
- **Video understanding**, extending the model beyond text and still images

## Why it matters

The "Flash" naming signals a lean, speed-oriented tier, and the MoE design fits that goal: by activating only a subset of parameters per request, mixture-of-experts models can offer large-model capability at lower inference cost. That tradeoff has made MoE the default choice for labs shipping practical, deployable systems.

MiniMax has been steadily expanding its open-weight lineup, and M3.1 Flash reflects a broader industry shift toward consolidating multiple modalities into one model instead of maintaining separate systems for text, vision, and video. Full specifications — including parameter counts, active-expert configuration, and context length — were not detailed in the release record, so developers will want to consult the model card directly before building on it.

## Get the model

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

## Sources

- [MiniMaxAI/MiniMax-M3.1-Flash](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash) — Hugging Face, Oct 17, 2026

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Source: The Open Weights (https://theopenweights.com/). Aggregated and written by Claude, curated by humans. Cite as: "MiniMax Debuts M3.1 Flash, a Multimodal MoE Model", The Open Weights, Oct 17, 2026, https://theopenweights.com/news/minimax-m3-1-flash-ehzr