MiniMax M2

MiniMax M2

MiniMax
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+

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About

Introducing DeepSeek-V3.2-Exp, our latest experimental model built on V3.1-Terminus, debuting DeepSeek Sparse Attention (DSA) for faster and more efficient inference and training on long contexts. DSA enables fine-grained sparse attention with minimal loss in output quality, boosting performance for long-context tasks while reducing compute costs. Benchmarks indicate that V3.2-Exp performs on par with V3.1-Terminus despite these efficiency gains. The model is now live across app, web, and API. Alongside this, the DeepSeek API prices have been cut by over 50% immediately to make access more affordable. For a transitional period, users can still access V3.1-Terminus via a temporary API endpoint until October 15, 2025. DeepSeek welcomes feedback on DSA via its feedback portal. In conjunction with the release, DeepSeek-V3.2-Exp has been open-sourced: the model weights and supporting technology (including key GPU kernels in TileLang and CUDA) are available on Hugging Face.

About

MiniMax M2 is an open source foundation model built specifically for agentic applications and coding workflows, striking a new balance of performance, speed, and cost. It excels in end-to-end development scenarios, handling programming, tool-calling, and complex, long-chain workflows with capabilities such as Python integration, while delivering inference speeds of around 100 tokens per second and offering API pricing at just ~8% of the cost of comparable proprietary models. The model supports “Lightning Mode” for high-speed, lightweight agent tasks, and “Pro Mode” for in-depth full-stack development, report generation, and web-based tool orchestration; its weights are fully open source and available for local deployment with vLLM or SGLang. MiniMax M2 positions itself as a production-ready model that enables agents to complete independent tasks, such as data analysis, programming, tool orchestration, and large-scale multi-step logic at real organizational scale.

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

Researchers and AI engineers looking for a solution providing a model that performs well on long-context tasks with reduced compute cost

Audience

Software engineering teams, AI practitioners and developer-led organizations requiring a tool offering a model optimized for agent workflows and full-stack coding tasks

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

Free
Free Version
Free Trial

Pricing

$0.30 per million input tokens
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

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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

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io/news/minimax-m2

Alternatives

Alternatives

DeepSeek-V3.2

DeepSeek-V3.2

DeepSeek
Devstral 2

Devstral 2

Mistral AI
MiniMax M2

MiniMax M2

MiniMax
Devstral Small 2

Devstral Small 2

Mistral AI
MiniMax M2.5

MiniMax M2.5

MiniMax
DeepSeek-V4

DeepSeek-V4

DeepSeek
MiniMax M2.7

MiniMax M2.7

MiniMax

Categories

Categories

Integrations

DeepSeek
Claude Code
Cline
Hugging Face
Kilo Code
NVIDIA DRIVE
Okara
OpenAI
Python
Shiori

Integrations

DeepSeek
Claude Code
Cline
Hugging Face
Kilo Code
NVIDIA DRIVE
Okara
OpenAI
Python
Shiori
Claim DeepSeek-V3.2-Exp and update features and information
Claim DeepSeek-V3.2-Exp and update features and information
Claim MiniMax M2 and update features and information
Claim MiniMax M2 and update features and information