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What is MiniMax M2.5?

MiniMax M2.5 is an advanced frontier model designed to deliver real-world productivity across coding, search, agentic tool use, and high-value office tasks. Built on large-scale reinforcement learning across hundreds of thousands of structured environments, it achieves state-of-the-art results on benchmarks such as SWE-Bench Verified, Multi-SWE-Bench, and BrowseComp. The model demonstrates architect-level planning capabilities, decomposing system requirements before generating full-stack code across more than ten programming languages including Go, Python, Rust, TypeScript, and Java. It supports complex development lifecycles, from initial system design and environment setup to iterative feature development and comprehensive code review. With native serving speeds of up to 100 tokens per second, M2.5 significantly reduces task completion time compared to prior versions. Reinforcement learning enhancements improve token efficiency and reduce redundant reasoning rounds, making agentic workflows faster and more precise. The model is available in both M2.5 and M2.5-Lightning variants, offering identical intelligence with different throughput configurations. Its pricing structure dramatically undercuts other frontier models, enabling continuous deployment at a fraction of traditional costs. M2.5 is fully integrated into MiniMax Agent, where standardized Office Skills allow it to generate formatted Word documents, financial models in Excel, and presentation-ready PowerPoint decks. Users can also create reusable domain-specific “Experts” that combine industry frameworks with Office Skills for structured, professional outputs. Internally, MiniMax reports that M2.5 autonomously completes a significant portion of operational tasks, including a majority of newly committed code. By pairing scalable reinforcement learning, high-speed inference, and ultra-low cost, MiniMax M2.5 positions itself as a production-ready engine for complex agent-driven applications.

What is Hy3?

The Hy3 preview showcases Tencent Hy's latest and most sophisticated model within the Hy series, boasting an impressive 295 billion parameters arranged in a Mixture-of-Experts framework, with 21 billion parameters activated and a remarkable 3.8 billion allocated to the MTP layer, all while supporting a vast context window of up to 256,000 tokens. This innovative model marks a significant milestone as it utilizes Tencent Hy's newly enhanced infrastructure, which is specifically designed to improve its effectiveness in various practical applications such as complex reasoning, following directives, contextual learning, coding assignments, and overall inference skills. By blending swift and comprehensive cognitive processing, it can provide clear responses for basic questions while also allowing for detailed analysis of complex mathematical, programming, and logical problems. The model is engineered to demonstrate extensive capabilities in comprehending lengthy contexts, following instructions accurately, utilizing tools effectively, and executing agent workflows with precision, with evaluations performed not only against traditional benchmarks but also in realistic business and development scenarios. Additionally, its versatile design allows for effective adaptation across a wide array of situations, significantly expanding its potential for use in numerous applications, thus making it a vital tool in advancing the field.

Media

Media

Integrations Supported

APIFree
Alibaba AI Coding Plan
BLACKBOX AI
Claude Code
Clawd.run
Cline
Fireworks AI
Kilo Code
Ollama
OpenClaw
Oxlo.ai
Roo Code
Shiori
Tabbit Browser

Integrations Supported

Tencent Hy

API Availability

Has API

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

MiniMax

Date Founded

2021

Company Location

Singapore

Company Website

www.minimax.io

Company Facts

Organization Name

Tencent

Date Founded

1998

Company Location

China

Company Website

hy.tencent.com/research/hy3-preview

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

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