Hy4

Hy4

Tencent
+
+

Related Products

  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Checksum.ai
    1 Rating
    Visit Website
  • QuantaStor
    6 Ratings
    Visit Website
  • Lockbox LIMS
    72 Ratings
    Visit Website
  • Bitdefender Ultimate Small Business Security
    5 Ratings
    Visit Website
  • AddSearch
    140 Ratings
    Visit Website
  • Pipefy
    592 Ratings
    Visit Website
  • Visual Planning
    117 Ratings
    Visit Website
  • Dialpad Support
    1,600 Ratings
    Visit Website
  • Orca Security
    606 Ratings
    Visit Website

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.

About

Muse Spark 1.2 is Meta’s coding-focused model update designed to power Muse Code and improve software engineering workflows. The model is built for code generation, complex debugging, codebase understanding, long-horizon development tasks, and end-to-end developer workflows. Muse Spark 1.2 was co-trained with Muse Code to improve performance inside the terminal coding agent environment. It supports planning, goal conditioning, context compaction, subagent coordination, and iterative coding workflows across large repositories. The model was trained with expanded coding compute, diverse development environments, self-improvement loops, and long-running engineering tasks. Built for AI developers and software teams, Muse Spark 1.2 helps agents plan, write, validate, debug, and optimize code with greater autonomy.

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

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

Audience

AI developers, software engineers, coding agent builders, research teams, platform teams, DevOps teams, ML engineers, enterprise development teams, and organizations that need code generation, debugging, codebase understanding, long-horizon coding, terminal agents, subagent coordination, repository automation, kernel optimization, and end-to-end developer workflow support

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

No information available.
Free Version
Free Trial

Pricing

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Spark 1.2 looks like a big step up for developers because it is clearly aimed at real software engineering work, not just casual code suggestions. The fact that it powers Muse Code makes it feel more practical right away, especially for terminal-based workflows where the model can help write code, validate changes, and work through bigger tasks. I like that Meta seems to be pushing hard into agentic coding. Earlier Muse Spark versions were already positioned around multimodal reasoning, tool use, and visual coding, and 1.2 feels like the more developer-focused evolution of that direction. The cost angle is interesting too. Reports mention Muse Code having multiple pricing tiers, including a cheaper option, which could matter a lot for developers running coding agents frequently instead of only using AI once in a while.

Cons

  • It is still new and tied to a beta coding agent, so I would not trust it blindly yet. I would want to test it on real repos, messy bugs, failing tests, multi-file edits, and longer agent runs before making it part of my daily stack. Meta also still has to prove the developer experience. A strong model is one thing, but coding agents live or die on tooling, speed, reliability, permissions, logs, diffs, and how well they recover when something breaks.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

Meta
Founded: 2004
United States
meta.ai

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

Categories

Categories

Integrations

C#
Claude Agent SDK
Claude Code
Continue
Dart
Go
HTML
Hermes Agent
JavaScript
Kotlin
Kubernetes
LangChain
LlamaIndex
Lua
Muse Video
OpenAI Agents SDK
OpenClaw
PHP
PowerShell
Python

Integrations

C#
Claude Agent SDK
Claude Code
Continue
Dart
Go
HTML
Hermes Agent
JavaScript
Kotlin
Kubernetes
LangChain
LlamaIndex
Lua
Muse Video
OpenAI Agents SDK
OpenClaw
PHP
PowerShell
Python
Claim Hy4 and update features and information
Claim Hy4 and update features and information
Claim Muse Spark 1.2 and update features and information
Claim Muse Spark 1.2 and update features and information