MiniMax M1MiniMax
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SubQSubquadratic
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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.
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About
SubQ is a large language model developed by Subquadratic, designed specifically for long-context reasoning tasks. It can process up to 12 million tokens in a single prompt, allowing it to analyze entire codebases, long histories, and complex datasets at once. The model uses a sub-quadratic sparse-attention architecture that improves efficiency by focusing only on the most relevant relationships in the data. This approach reduces computational overhead while maintaining strong performance on large-scale tasks. SubQ is optimized for use cases such as software engineering, coding agents, and long-context retrieval. It delivers fast processing speeds and operates at a lower cost compared to many traditional models. Developers can access SubQ through APIs or integrate it into coding tools for enhanced workflows. Its architecture enables scalable AI reasoning without the limitations of standard transformer models.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
AI researchers, developers, and enterprises needing a solution providing LLM capable of long‑context reasoning, efficient compute, and integration via function calls
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Audience
Developers, AI engineers, and enterprises that need large-context language models for coding, data analysis, and advanced AI workflows
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
Supported
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API
Offers API
Supported
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API
Offers API
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Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationMiniMax
Founded: 2021
Singapore
www.minimax.io/news/minimaxm1
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Company InformationSubquadratic
Founded: 2026
United States
subq.ai/
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Categories |
Categories |
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Integrations
Anuma
Supported
Claude Code
Not Supported
GitHub
Supported
Hugging Face
Supported
OpenAI
Not Supported
OpenAI Codex
Not Supported
SiliconFlow
Supported
SubQ 1.1 Small
Not Supported
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Integrations
Anuma
Not Supported
Claude Code
Supported
GitHub
Not Supported
Hugging Face
Not Supported
OpenAI
Supported
OpenAI Codex
Supported
SiliconFlow
Not Supported
SubQ 1.1 Small
Supported
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