Hy4

Hy4

Tencent
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Google AI Studio
    30 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • InEight
    136 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website
  • Unimus
    33 Ratings
    Visit Website
  • Dialpad Support
    1,600 Ratings
    Visit Website
  • Criminal IP ASM
    21 Ratings
    Visit Website
  • AthenaHQ
    36 Ratings
    Visit Website

About

DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.

About

Hy4 preview is a new-generation open source Mixture-of-Experts flagship model built for real-world productivity tasks across software engineering, office work, game development, and scientific research. The model contains 770B total parameters with 49B activated per token and supports a 1M-token context window, giving it the capacity to work through large codebases, extensive document collections, and long multi-step tasks. Its 78-layer architecture combines Gated DeepSeek Sparse Attention with IndexCache for cross-layer sparse index reuse and identity Hyper-Connections to expand information flow between layers. A native Multi-Token Prediction layer is included for speculative decoding. Hy4 preview is designed to understand, plan, debug, and verify long-horizon engineering tasks, with additional gains in front-end visual quality and interaction design.

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 seeking a powerful open-source language model for large-scale reasoning, coding, and long-context AI applications

Audience

Developers, researchers, and technical professionals seeking an AI model for coding, document work, game development, scientific reasoning, and complex productivity 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

$0.435 per 1M tokens (input)
$0.435 per 1 million input tokens (cache miss), $0.003625 per 1 million input tokens (cache hit), and $0.87 per 1 million output tokens
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5

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

Pros & Cons from Real Users

Pros

  • DeepSeek-V4-Pro is one of those models I keep coming back to because it handles serious work without feeling ridiculously expensive. For coding, repo analysis, long debugging threads, and agent-style workflows, the 1M-token context window is a huge advantage. I also like that it feels strong across both reasoning and implementation. I can use it to think through architecture, explain a messy bug, generate a fix, write tests, and then sanity-check the tradeoffs without constantly switching models. The Pro-Max reasoning mode is especially useful when I need it to slow down and really work through something. It is not the mode I would use for every quick answer, but for hard technical problems, it gives the model a lot more room to reason. The open-weight angle is a big plus too. As someone who uses it heavily, I like having more flexibility than a purely closed API model gives me.

Cons

  • It is still not something I would run on autopilot. For production code, I always review diffs, run tests, and check edge cases because even strong models can make confident mistakes. It can also be overkill for simple tasks. If I just need a quick explanation, small script, or lightweight edit, DeepSeek-V4-Flash may be the better fit. The size is another consideration. Open weights are great, but self-hosting a 1.6T-parameter MoE model is not casual infrastructure.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

Tencent
Founded: 1998
China
hy.tencent.ai/research/hy4-preview

Alternatives

Grok 4.6

Grok 4.6

SpaceXAI

Alternatives

Grok 4.6

Grok 4.6

SpaceXAI
Claude Opus 5

Claude Opus 5

Anthropic
Claude Opus 5

Claude Opus 5

Anthropic
Claude Fable 5

Claude Fable 5

Anthropic
Claude Fable 5

Claude Fable 5

Anthropic
DeepSeek-V4

DeepSeek-V4

DeepSeek

Categories

Categories

Integrations

Bash
Buda
C#
C++
CSS
ClinePass
DeepSeek Harness
Go
Java
Novita AI
OpenClaw
OpenTag
Oxlo.ai
Python
R
Ruby
Vercel AI Gateway
XML
YAML
ZooClaw

Integrations

Bash
Buda
C#
C++
CSS
ClinePass
DeepSeek Harness
Go
Java
Novita AI
OpenClaw
OpenTag
Oxlo.ai
Python
R
Ruby
Vercel AI Gateway
XML
YAML
ZooClaw
Claim DeepSeek-V4-Pro and update features and information
Claim DeepSeek-V4-Pro and update features and information
Claim Hy4 and update features and information
Claim Hy4 and update features and information