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Description

Hy4 preview represents a cutting-edge open source Mixture-of-Experts flagship model tailored for a variety of real-world productivity tasks, including software engineering, office activities, game development, and scientific exploration. This model boasts a staggering total of 770 billion parameters, with 49 billion activated per token, and features an impressive 1 million-token context window, allowing it to efficiently manage large codebases, vast document collections, and complex multi-step processes. The architecture consists of 78 layers that integrate Gated DeepSeek Sparse Attention alongside IndexCache for reusing sparse indices across layers, while also employing identity Hyper-Connections to enhance the flow of information between layers. Additionally, a dedicated Multi-Token Prediction layer facilitates speculative decoding, further enhancing its capabilities. Hy4 preview is crafted to comprehend, plan, debug, and validate intricate engineering projects, while also achieving notable improvements in the quality of front-end visuals and interaction design, thereby making it an invaluable asset for professionals across various domains.

Description

MAI-Code-1.1-Flash is a compact and effective coding model aimed at enhancing the speed and quality of code development for engineering teams. Currently implemented in GitHub Copilot and integrated into VS Code, it caters to the actual workflows of developers, specifically enhancing command-line operations and .NET tasks based on user input. When compared to the version unveiled at Microsoft Build in June, this model showcases a significant improvement in code quality, achieved with reduced token usage and quicker streaming responses. Microsoft claims a 22% enhancement on Terminal-Bench 2.1 for GitHub Copilot CLI and a 15% boost in .NET task performance. Additionally, production outcomes indicate a 4% rise in code survival rates and a 9% increase in users returning to the platform. Notably, in GitHub Copilot, tokens are streamed 25% faster, and the model requires 25% fewer tokens for task completion, which translates to quicker responses, reduced wait times, and enhanced productivity from each token processed. These advancements stem from refined training methods and improved operational efficiencies, with a strong focus on practical application in real-world scenarios. Ultimately, MAI-Code-1.1-Flash represents a significant leap forward in coding assistance technology.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

.NET
GitHub Copilot
Microsoft Azure
Microsoft Foundry
Tencent Hy
Visual Studio Code

Integrations

.NET
GitHub Copilot
Microsoft Azure
Microsoft Foundry
Tencent Hy
Visual Studio Code

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Tencent

Founded

1998

Country

China

Website

hy.tencent.ai/research/hy4-preview

Vendor Details

Company Name

Microsoft AI

Founded

2024

Country

United States

Website

microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/

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