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MiniMax open-sources M3.1 Flash model weights

7 reports1 discussions8 story updatesUpdated Oct 24 05:02

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Latest development · Report

MiniMax M3.1 Flash Launches on Tenstorrent Cloud

Developments

2 confirmed developments

  1. MiniMax M3.1 Flash launches on Tenstorrent Cloud

    Source:MiniMax
  2. MiniMax open-sources M3.1 Flash model weights

    Source:MiniMax

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Oct 24

  1. MiniMaxFirst-party

    MiniMax M3.1 Flash Launches on Tenstorrent Cloud

    MiniMax announced that MiniMax M3.1 Flash is now available on Tenstorrent Cloud, can run on Tensix chips, and supports Ethernet scale-out and an open-source technology stack. Tenstorrent's quoted post stated that MiniMax released the open weights of this model on the same day, and users can try it in the playground or connect it to their own agent harness.

  2. English text is being prepared.Related discussion

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    This post contributes to heat; it is not a formal report or confirmed fact.

Oct 23

  1. Testing CatalogSelected

    MiniMax publicly releases M3.1 Flash weights on Hugging Face

    MiniMax has publicly released the MiniMax M3.1 Flash weights on Hugging Face; the model has 428B total parameters and 23B activated per token. The company claims generational improvements in agent tasks, coding, and cybersecurity, with scores of 76.2 on BankerToolBench, 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 29.6 on Agents' Last Exam, and 82.2 on CyberGym. This model is the stealth model Space Bunny on OpenRouter, released on October 19, and is now available on the MiniMax platform and API.

  2. IT Home · Artificial Intelligence

    MiniMax Open-Sources M3.1 Flash Model Weights with 428B Total Parameters

    English text is being prepared.

  3. Testing Catalog

    October 23 AI Daily: MiniMax open-sources M3.1 Flash, OpenAI launches Decisions API

    MiniMax open-sources M3.1 Flash, a 428B-parameter MoE with 23B activated parameters, gaining day-one support from Together, SGLang, vLLM and NVIDIA NeMo. OpenAI's Decisions API is officially available, powered by GPT-6 Luna, with classification and decision speed improved by up to 10x, at an input price of $0.10 per million tokens. Anthropic's Claude models are officially available on Google Cloud, and starting next week, Claude sessions on Pro, Max and Team plans will run in auto mode by default.

  4. The Paper

    MiniMax open-sources the M3.1 Flash model, reducing usage cost by 70%

    MiniMax announced on October 23 the open-sourcing of the M3.1 Flash model, which processed over 100 trillion tokens within 72 hours of launch. Compared with the previous generation M3, M3.1 Flash has comprehensively improved capabilities, with usage cost reduced by 70% and online inference speed increased by nearly 3 times. MiniMax stated it will work with chip manufacturers such as Huawei Ascend, NVIDIA, and AMD, as well as inference frameworks and communities such as vLLM, SGLang, and Hugging Face, to advance day-one open-source integration.

  5. MiniMaxFirst-partySelected

    MiniMax Opens M3.1 Flash Model Weights

    MiniMax has announced that the model weights for M3.1 Flash are now open. Together AI, a day-one launch partner, has deployed the model in its AI Native Cloud production environment, so users do not need to manage GPUs themselves. According to Together AI, M3.1 Flash targets agentic tasks, coding, computer use, and cybersecurity scenarios, and supports a 1M context window and vision capabilities.

  6. MiniMaxFirst-partySelected

    MiniMax M3.1 Flash releases open-source weights, 428B total parameters, 23B activated per token

    MiniMax M3.1 Flash weights are now public, with 428B total parameters and 23B activated per token. The company claims substantial improvements in agentic tasks, coding, and cybersecurity: BankerToolBench 76.2, DeepSWE v1.1 73.7%, OSWorld V2 61.7, Agents' Last Exam 29.6, CyberGym 82.2. The model uses MiniMax Sparse Attention and DSpark speculative decoding to improve inference efficiency; the weights are now available on Hugging Face and ModelScope, with API and MCode desktop entry points also provided.

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