GLM-5.2

GLM-5.2

Zhipu AI
MAI-Code-1.1-Flash

MAI-Code-1.1-Flash

Microsoft 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

MAI-Code-1.1-Flash is a small, efficient coding model designed to help engineering teams write better code faster. Now in production in GitHub Copilot and built into VS Code, it focuses on real-world developer workflows, with particular improvements for command-line tasks and .NET development based on developer feedback. Compared with the version introduced at Microsoft Build in June, the model produces higher-quality code while using fewer tokens and streaming responses faster. Microsoft reports a 22% improvement on Terminal-Bench 2.1 in GitHub Copilot CLI and a 15% improvement on .NET tasks. Production results also showed a 4% increase in code survival and a 9% increase in return visits. In GitHub Copilot, tokens stream 25% faster and the model uses 25% fewer tokens to complete a task, aiming to deliver faster answers, less waiting, and more useful work from every token. Its gains come from improved training and serving efficiency, with optimization centered on real-world use.

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

Software engineering teams and developers seeking to write and complete code faster with an efficient AI coding model integrated into their development workflow

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

No information available.
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 4.0 / 5
features 4.0 / 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

  • The agentic coding angle is the best part. It can plan, reason, and execute across coding tasks, which makes it useful beyond simple autocomplete. I also like the screenshot-to-prototype feature. Being able to understand screenshots, diagrams, and designs could save a lot of time when turning UI ideas into working code.

Cons

  • The main downside is that I would still review everything carefully. Even a strong coding model can make bad assumptions, miss edge cases, or produce code that looks right but fails in a real project.

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

Microsoft AI
Founded: 2024
United States
microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/

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Categories

Categories

Integrations

.NET
Amp
Cherry Studio
Claude Code
Cosmos
Dessix
Factory Droid
Hermes Agent
JetBrains Junie
Kotlin
LM Studio Bionic
Ollama
PHP
PyTorch
Rust
Sup AI
Tabbit Browser
Vercel AI Gateway
Wafer
Z.ai

Integrations

.NET
Amp
Cherry Studio
Claude Code
Cosmos
Dessix
Factory Droid
Hermes Agent
JetBrains Junie
Kotlin
LM Studio Bionic
Ollama
PHP
PyTorch
Rust
Sup AI
Tabbit Browser
Vercel AI Gateway
Wafer
Z.ai
Claim GLM-5.2 and update features and information
Claim GLM-5.2 and update features and information
Claim MAI-Code-1.1-Flash and update features and information
Claim MAI-Code-1.1-Flash and update features and information