GLM-5.2

GLM-5.2

Zhipu AI
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About

GLM-5.2 is an advanced AI foundation model designed to support complex reasoning, coding, and long-range agentic tasks. It helps developers, teams, and organizations build intelligent systems that can understand instructions, solve technical problems, and assist with demanding workflows. The model is especially useful for software engineering, automation, research, and productivity-focused applications. GLM-5.2 is built to handle large amounts of context, making it suitable for projects that require deeper understanding across extended conversations, documents, or codebases. Its mixture-of-experts design helps balance strong performance with more efficient model operation. GLM-5.2 gives businesses and developers a powerful AI tool for creating smarter applications, improving technical workflows, and supporting advanced digital experiences.

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, AI teams, software companies, enterprises, and technical organizations that need advanced reasoning, coding, automation, and agentic AI capabilities

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

No images available

Screenshots and Videos

Pricing

Free
Open source
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 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

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

Pros & Cons from Real Users

Pros

  • GLM-5.2 has been excellent for building AI agents and handling coding workflows. It follows complex instructions well, breaks down tasks clearly, and stays reliable across multi-step agentic work. For coding, it is fast, practical, and good at understanding context. I use it for debugging, refactoring, generating functions, and planning larger software tasks, and it consistently gives useful output. It also feels strong for tool-use and automation-style workflows. When I need an AI model to reason through steps, produce structured responses, or support agent behavior, GLM-5.2 performs very well.

Cons

  • Like any model, it still benefits from clear prompts and good context. For very large or highly specific codebases, I sometimes need to guide it with extra details.

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

Zhipu AI
Founded: 2023
China
z.ai/

Company Information

Meta
Founded: 2004
United States
meta.ai

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Categories

Categories

Integrations

C
C#
C++
Claude Code
Go
HTML
Hermes Agent
Java
JavaScript
Kotlin
OpenClaw
PHP
Python
R
Rust
SQL
Swift
TypeScript
Bash
OpenRouter

Integrations

C
C#
C++
Claude Code
Go
HTML
Hermes Agent
Java
JavaScript
Kotlin
OpenClaw
PHP
Python
R
Rust
SQL
Swift
TypeScript
Bash
OpenRouter
Claim GLM-5.2 and update features and information
Claim GLM-5.2 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