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GLM : China's Most Advanced AI Coding Model (GLM 4.6)

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.

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.

Example: Create a React component for a user dashboard with charts

Technical Context

Specify programming language, framework, libraries, and technical stack for coding tasks.

Example: Using React 18, TypeScript, Tailwind CSS, and Recharts

Code Style & Conventions

Define coding standards, naming conventions, and architectural patterns you prefer.

Example: Use functional components, hooks, and follow Airbnb style guide

Translation Requirements

For translation tasks, specify source/target languages, tone, formality, and cultural context.

Example: Translate to casual French for social media, maintain friendly tone

Output Format

Specify the desired output structure, whether code, JSON, markdown, or formatted text.

Example: Return as JSON with 'code', 'explanation', and 'usage' fields

Constraints & Requirements

Define limitations, dependencies, performance needs, or specific requirements to consider.

Example: Must support mobile, accessible (WCAG AA), and load under 2s

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

✗
Basic Prompt

"Write a login function"

✓
Enhanced Prompt

"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."

✗
Basic Prompt

"Translate this to Japanese"

✓
Enhanced Prompt

"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."

✗
Basic Prompt

"Build a dashboard"

✓
Enhanced Prompt

"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."

How to Use GLM-4.6

Start leveraging GLM-4.6's powerful capabilities for your coding, translation, and intelligent agent tasks.

1

Define Your Task

Clearly describe what you want to achieve with context

2

Craft Your Prompt

Use detailed prompts with technical specs and requirements

3

Enable Features

Activate deep thinking, function calling, or structured output as needed

4

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.

FAQ

Frequently Asked Questions

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