GLM-4.6:
China's Most Advanced AI Coding Model
GLM-4.6 is Zhipu AI's flagship model with 355B total parameters and 32B activated parameters. It delivers exceptional coding capabilities rivaling Claude Sonnet 4, features a 200K context window for handling complex tasks, enhanced intelligent search, and superior multilingual translation. Designed for developers, enterprises, and creators seeking cutting-edge AI performance.
What is GLM-4.6?
GLM-4.6 is Zhipu AI's latest flagship model launched in 2025, featuring 355B total parameters with 32B activated parameters. Built on advanced MoE (Mixture of Experts) architecture, GLM-4.6 represents a significant leap in AI capabilities, surpassing GLM-4.5 across all core competencies. It excels in code generation, deep reasoning, intelligent search, and multilingual translation, making it the leading domestic AI model for professional applications.
Advanced coding capabilities rivaling Claude Sonnet 4
200K context window for complex code and agent tasks
Enhanced reasoning with deep thinking mode support
Superior intelligent search and tool calling
Multilingual translation optimized for small languages
Improved writing quality and role-playing scenarios
Function calling with tool integration
Structured JSON output for system integration
Key Features of GLM-4.6
GLM-4.6 combines cutting-edge AI technology with practical features for developers and enterprises.
Advanced Coding
Industry-leading code generation aligned with Claude Sonnet 4. Supports Python, JavaScript, Java, and more with beautiful frontend layouts and logical structure.
Deep Reasoning
Enhanced reasoning capabilities with deep thinking mode. Provides comprehensive analysis and supports tool calling during reasoning processes.
Intelligent Search
Strengthened tool calling and search agent performance. Better intent understanding, tool retrieval, and result integration for deep research scenarios.
Multilingual Translation
Optimized translation for small languages (French, Russian, Japanese, Korean). Perfect for social media, e-commerce content, and cross-border applications.
Long Context Window
200K token context window expanded from 128K. Handles longer code files, documents, and complex multi-step agent tasks with ease.
Creative Writing
Enhanced writing quality in style, readability, and role-playing. Supports novels, scripts, copywriting with natural expression and emotional control.
Function Calling
Powerful tool calling capabilities with MCP support. Flexibly invoke external tools and data sources to extend application scenarios.
Structured Output
Native JSON formatting support for structured data output. Seamlessly integrate with systems and APIs for automated workflows.
How to Write Effective GLM-4.6 Prompts
Master prompt engineering to unlock GLM-4.6's full potential. Learn techniques for coding, translation, and intelligent agent tasks.
Essential Prompt Elements
Task Description
Clearly state what you want to achieve. Be specific about the goal, context, and expected outcome.
Technical Context
Specify programming language, framework, libraries, and technical stack for coding tasks.
Code Style & Conventions
Define coding standards, naming conventions, and architectural patterns you prefer.
Translation Requirements
For translation tasks, specify source/target languages, tone, formality, and cultural context.
Output Format
Specify the desired output structure, whether code, JSON, markdown, or formatted text.
Constraints & Requirements
Define limitations, dependencies, performance needs, or specific requirements to consider.
Pro Tips for Better Results
Be Specific for Coding
Instead of 'create a form,' try 'create a multi-step registration form with email validation, password strength meter, and smooth transitions between steps using React Hook Form'
Provide Context for Translation
Include target audience, platform, and cultural context. For example: 'Translate for Japanese Gen-Z users on Instagram, use casual language with trending expressions'
Break Down Complex Tasks
For agent tasks, outline the workflow step by step. Enable deep thinking mode for complex problems requiring comprehensive reasoning and analysis
Leverage Function Calling
Describe available tools and when to use them. For search tasks, specify which APIs to call and how to integrate results for coherent answers
Good vs. Better Prompts
"Write a login function"
"Create a secure login function in TypeScript using JWT authentication, bcrypt password hashing, rate limiting (5 attempts per 15 minutes), and return proper error messages for invalid credentials, expired tokens, or locked accounts. Include TypeScript types and JSDoc comments."
"Translate this to Japanese"
"Translate the following marketing copy to Japanese for a tech-savvy audience aged 25-35. Maintain a professional yet approachable tone, use modern business Japanese (avoiding overly formal keigo), and adapt any cultural references to resonate with Japanese consumers. Text: [your text]"
"Build a dashboard"
"Build a responsive admin dashboard using React 18, TypeScript, and Tailwind CSS. Include: (1) Sidebar navigation with collapsible menu, (2) Top bar with user profile and notifications, (3) Main content area with grid layout for cards showing KPIs, (4) Charts using Recharts for data visualization, (5) Dark mode support, (6) Mobile-responsive with hamburger menu. Follow modern component patterns with proper TypeScript types."
ประวัติเวอร์ชัน GLM
ติดตามวิวัฒนาการของโมเดล GLM ของ Zhipu AI ในแต่ละรุ่นที่นำเสนอความก้าวล้ำในการเขียนโค้ด การใช้เหตุผล และความสามารถทางภาษาที่หลากหลาย
ความก้าวหน้าครั้งสำคัญที่แสดงถึงโมเดลเรือธงของ Zhipu AI GLM-4.6 เหนือกว่า GLM-4.5 ในทุกความสามารถหลักด้วยประสิทธิภาพการเขียนโค้ดที่ปฏิวัติวงการ บริบทที่ขยาย การค้นหาที่ได้รับการปรับปรุง และการแปลภาษาที่เหนือกว่า ด้วยพารามิเตอร์รวม 355B และพารามิเตอร์ที่เปิดใช้งาน 32B ทำให้เป็นมาตรฐานใหม่สำหรับโมเดล AI ในประเทศในการใช้งานระดับมืออาชีพ
Key Improvements:
- •ความสามารถในการเขียนโค้ดขั้นสูงเทียบเท่า Claude Sonnet 4 - โมเดลชั้นนำในประเทศ
- •ขยาย Context Window จาก 128K เป็น 200K tokens
- •ปรับปรุงการใช้เหตุผลด้วยโหมด Deep Thinking ที่รองรับการเรียกใช้เครื่องมือระหว่างการอนุมาน
- •เสริมสร้างการค้นหาอัจฉริยะและการดึงเครื่องมือเพื่อประสิทธิภาพของเอเจนต์ที่ดียิ่งขึ้น
- •ปรับปรุงการแปลภาษาให้เหมาะสมสำหรับภาษาขนาดเล็ก (ฝรั่งเศส รัสเซีย ญี่ปุ่น เกาหลี)
- •ปรับปรุงคุณภาพการเขียนในด้านสไตล์ ความสามารถในการอ่าน และสถานการณ์การสวมบทบาท
- •ประสิทธิภาพของ Token ดีขึ้น 30% เมื่อเทียบกับ GLM-4.5
- •สร้างโค้ดส่วนหน้าสวยงามด้วยเลย์เอาต์ขั้นสูง
- •รองรับ MCP สำหรับการรวมเครื่องมือภายนอกและแหล่งข้อมูลที่ยืดหยุ่น
- •การจัดรูปแบบ JSON แบบ Native สำหรับเอาต์พุตที่มีโครงสร้าง
- •ประสิทธิภาพที่เหนือกว่าในระบบอัตโนมัติสำนักงานและการสร้าง PPT
- •ปรับปรุงความสามารถในการประมวลผลงานข้ามภาษา
Performance:
บริบท 200K, เอาต์พุตสูงสุด 128K, การเขียนโค้ดเทียบเท่า Claude Sonnet 4, คะแนนสูงสุดใน AIME/GPQA/LCB/SWE-Bench
GLM-4.6 Performance Benchmarks
GLM-4.6 performance metrics based on comprehensive testing across 8 authoritative benchmarks.
| Benchmark | Score | Description |
|---|---|---|
| AIME 25 | Leading | Advanced mathematical reasoning |
| GPQA | Top Tier | Graduate-level question answering |
| LCB v6 | Excellent | Long context benchmark |
| HLE | Superior | Human-level evaluation |
| SWE-Bench Verified | Outstanding | Real-world software engineering |
| Claude Code Tasks | 74/74 | Real programming scenario testing |
| Token Efficiency | 30% Less | Compared to GLM-4.5 |
| Context Window | 200K | Extended from 128K tokens |
Metrics based on GLM-4.6 testing in 2025. Performance aligned with Claude Sonnet 4, leading among domestic models. All test trajectories publicly available for verification.
GLM-4.6 Use Cases
Discover how professionals leverage GLM-4.6 for innovative AI applications across industries.
AI Coding & Development
Cover Python, JavaScript, Java, and mainstream languages. Beautiful frontend code, reasonable layouts, and logical structure. Native support for agent tasks with strong autonomous planning.
Smart Office Automation
Significantly enhanced PPT creation and office automation. Generate advanced, beautiful layouts while maintaining content integrity and expression accuracy.
Multilingual Translation
Optimized for small languages and informal contexts. Perfect for social media, e-commerce, and short drama translation with style transfer and localization.
Content Creation
Support diverse content production including novels, scripts, and copywriting. Natural expression through context expansion and emotion control.
Virtual Characters & Chatbots
Maintain consistent tone and behavior across multi-turn dialogues. Ideal for virtual assistants, social AI, and brand personification with authentic interaction.
Intelligent Search & Research
Enhanced user intent understanding, tool retrieval, and result fusion. Support deep research scenarios with insightful answers and comprehensive analysis.
Enterprise Solutions
Build intelligent customer service, knowledge bases, and business automation systems. Reliable performance with data security and compliance support.
Education & Training
Create personalized learning content, answer student questions, and generate educational materials. Adapt to different learning styles and levels.
How to Use GLM-4.6
Start leveraging GLM-4.6's powerful capabilities for your coding, translation, and intelligent agent tasks.
Define Your Task
Clearly describe what you want to achieve with context
Craft Your Prompt
Use detailed prompts with technical specs and requirements
Enable Features
Activate deep thinking, function calling, or structured output as needed
Review & Iterate
Refine results and iterate based on output quality
Tips for Best Results
- •For coding tasks, specify the exact tech stack, libraries, and coding standards you want to follow
- •Use deep thinking mode for complex problems requiring comprehensive reasoning and analysis
- •Leverage the 200K context window for long code reviews, document analysis, or multi-step agent workflows
- •For translation, provide cultural context and target audience to get natural, localized results
- •Enable function calling when you need to integrate external tools, APIs, or data sources
- •Request structured JSON output for seamless system integration and automated processing
GLM-4.6 is designed for professional applications with enterprise-grade reliability and performance. Available through Zhipu AI's API platform.
Frequently Asked Questions
Everything you need to know about GLM-4.6, from capabilities to access and integration.
How does GLM-4.6 compare to other AI models?
GLM-4.6 rivals Claude Sonnet 4 in coding capabilities and leads among domestic Chinese models. In real programming tests (Claude Code environment with 74 tasks), GLM-4.6 achieved superior results while using 30% fewer tokens than GLM-4.5. It excels in comprehensive benchmarks including AIME, GPQA, LCB v6, and SWE-Bench Verified.
What makes GLM-4.6 special for coding tasks?
GLM-4.6 offers industry-leading code generation covering Python, JavaScript, Java, and more. It produces beautiful frontend code with reasonable layouts, maintains logical structure, and provides native support for agent tasks with strong autonomous planning and tool calling abilities. The 200K context window allows handling complex codebases and multi-file projects.
Can GLM-4.6 handle multilingual translation?
Yes, GLM-4.6 is optimized for multilingual translation, especially small languages like French, Russian, Japanese, and Korean. It excels in informal contexts such as social media, e-commerce content, and short drama translation, offering style transfer and localized expression for cross-border applications.
What is the deep thinking mode?
Deep thinking mode enables GLM-4.6 to perform comprehensive reasoning and analysis on complex problems. It can call tools during the reasoning process, providing deeper insights and more thorough solutions. This is particularly useful for challenging technical problems, research tasks, and strategic planning.
How do I access GLM-4.6?
GLM-4.6 is available through Zhipu AI's API platform at open.bigmodel.cn. You can access it via API calls, integrate it into your applications, or use it through supported development tools like Claude Code, Cline, and other mainstream programming environments.
What is the context window size?
GLM-4.6 features a 200K token context window, expanded from GLM-4.5's 128K. This allows you to work with longer code files, extensive documents, and complex multi-step agent tasks. The maximum output is 128K tokens, suitable for generating comprehensive content.
Does GLM-4.6 support function calling?
Yes, GLM-4.6 has powerful function calling capabilities with MCP (Model Context Protocol) support. You can flexibly invoke external tools, APIs, and data sources to extend application scenarios. It excels in tool retrieval, parameter extraction, and result integration.
Is GLM-4.6 suitable for enterprise applications?
Absolutely. GLM-4.6 is designed for professional and enterprise use with reliable performance, data security, and compliance support. It's ideal for building intelligent customer service, knowledge bases, business automation, and mission-critical applications requiring consistent quality.
Ready to Experience GLM-4.6?
Join developers and enterprises leveraging GLM-4.6 for advanced AI coding, intelligent search, and multilingual applications.