MiniMax M1

MiniMax M1

MiniMax
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About

MiniMax‑M1 is a large‑scale hybrid‑attention reasoning model released by MiniMax AI under the Apache 2.0 license. It supports an unprecedented 1 million‑token context window and up to 80,000-token outputs, enabling extended reasoning across long documents. Trained using large‑scale reinforcement learning with a novel CISPO algorithm, MiniMax‑M1 completed full training on 512 H800 GPUs in about three weeks. It achieves state‑of‑the‑art performance on benchmarks in mathematics, coding, software engineering, tool usage, and long‑context understanding, matching or outperforming leading models. Two model variants are available (40K and 80K thinking budgets), with weights and deployment scripts provided via GitHub and Hugging Face.

About

Qwen3.8-Flash-Next is an open-weight multimodal Mixture-of-Experts model and an early preview of the architecture planned for Qwen4. It systematically upgrades attention, residual connections, embeddings, and optimization to improve capability, computational efficiency, model capacity, and training stability. Its hybrid architecture combines Gated DeltaNet, which efficiently compresses historical information, with Qwen Sparse Attention, which selects important context at the micro-block level to reduce attention and indexing costs on long sequences. Gated Residual widens the residual stream into four branches and dynamically controls information flow across layers, while N-gram Embedding adds large-scale local-pattern memory with very little extra per-token computation and can be offloaded to host memory. The model uses a 125B-parameter main network plus 51B N-gram embedding parameters, while activating only 6B parameters per token.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers, developers, and enterprises needing a solution providing LLM capable of long‑context reasoning, efficient compute, and integration via function calls

Audience

Developers, researchers, and AI teams seeking to run or study an efficient multimodal open-weight model with long-context reasoning, coding, multilingual, and agentic capabilities

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$2 per 1M (input)
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io/news/minimaxm1

Company Information

Alibaba
Founded: 1999
China
qwen.ai/blog

Alternatives

MiniMax M3

MiniMax M3

MiniMax

Alternatives

GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
DeepSeek-V3.2

DeepSeek-V3.2

DeepSeek
Qwen3.5

Qwen3.5

Alibaba
OpenAI o1

OpenAI o1

OpenAI

Categories

Categories

Integrations

Hugging Face
Alibaba Cloud
Alibaba Cloud Model Studio
Anuma
Cherry Studio
Cline
GitHub
Happy Shrimp 1.0
ModelScope
Novita AI
Odysseus
OfoxAI
Ollama
OpenClaw
Python
Qwen
Qwen Code
QwenCloud
QwenWork
SiliconFlow

Integrations

Hugging Face
Alibaba Cloud
Alibaba Cloud Model Studio
Anuma
Cherry Studio
Cline
GitHub
Happy Shrimp 1.0
ModelScope
Novita AI
Odysseus
OfoxAI
Ollama
OpenClaw
Python
Qwen
Qwen Code
QwenCloud
QwenWork
SiliconFlow
Claim MiniMax M1 and update features and information
Claim MiniMax M1 and update features and information
Claim Qwen3.8-Flash-Next and update features and information
Claim Qwen3.8-Flash-Next and update features and information