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Try GLM-4.7 today and experience next-generation AI-powered code generation.
Overview
GLM-4.7 is a cutting-edge AI coding assistant developed by Zhipu AI, featuring 7 billion parameters specifically optimized for software development tasks. As part of the GLM-4 family, this model represents a significant advancement in AI-assisted programming, offering developers a powerful tool for code generation, debugging, refactoring, and technical problem-solving.
Built on advanced transformer architecture and trained on millions of code repositories across 40+ programming languages, GLM-4.7 demonstrates exceptional understanding of coding patterns, best practices, and software engineering principles. The model excels at generating clean, efficient, and production-ready code while maintaining strong context awareness across large codebases.
With its optimized 7B parameter architecture, GLM-4.7 strikes an ideal balance between performance and efficiency, making it accessible for individual developers, small teams, and large enterprises alike. Whether you're building web applications, mobile apps, backend services, or data science projects, GLM-4.7 provides intelligent assistance that accelerates development velocity.
Key Features
Multi-Language Code Generation
Generate high-quality code in 40+ programming languages including Python, JavaScript, Java, C++, Go, Rust, and more with context-aware suggestions.
Intelligent Debugging
Advanced error detection and debugging capabilities that identify bugs, suggest fixes, and explain root causes with detailed technical reasoning.
Auto Documentation
Automatically generate comprehensive documentation, docstrings, and code comments that explain functionality in clear, technical language.
Code Refactoring
Intelligent code refactoring that improves readability, performance, and maintainability while preserving functionality and following best practices.
Test Generation
Automated unit test generation with comprehensive coverage, edge case handling, and support for popular testing frameworks across languages.
Long Context Understanding
Process and understand large codebases with up to 128K tokens of context, maintaining awareness across multiple files and dependencies.
Pros & Cons
Advantages
- Exceptional code quality and accuracy
- Fast inference speed for real-time suggestions
- Support for 40+ programming languages
- Strong understanding of software architecture
- Excellent at explaining complex code
- Competitive pricing for API access
- Regular model updates and improvements
- Strong community and developer support
- Privacy-focused with data protection
- Seamless IDE integration options
Disadvantages
- Primarily Chinese-market focused initially
- Limited English documentation compared to competitors
- Newer model with smaller ecosystem
- Some niche languages have less training data
- Enterprise features still in development
Pricing
GLM-4.7 offers competitive and flexible pricing options designed for developers and teams of all sizes:
Free Tier
Perfect for individual developers and small projects. Includes 1M tokens per month with basic API access and community support.
Professional ($0.15/M tokens)
For professional developers and small teams. Higher rate limits, priority processing, email support, and advanced features.
Enterprise (Custom)
Tailored solutions for large organizations with custom pricing, dedicated support, SLA guarantees, on-premise deployment options, and volume discounts.
All plans include access to the full GLM-4.7 model with no feature restrictions. Volume discounts available for high-usage customers.
Best Use Cases
GLM-4.7 Excels For:
- Full-Stack Development: Building complete applications from frontend to backend with consistent code quality
- API Development: Creating RESTful APIs, GraphQL endpoints, and microservices with proper documentation
- Code Review: Automated code review and quality assurance with actionable suggestions for improvements
- Legacy Code Modernization: Refactoring and updating old codebases to modern standards and frameworks
- Learning and Education: Teaching programming concepts with detailed explanations and best practices
- Rapid Prototyping: Quickly building MVPs and proof-of-concept applications with production-ready code
May Not Be Ideal For:
- Teams requiring extensive English-only documentation
- Projects with extremely strict data residency requirements outside China/Asia
- Organizations needing mature enterprise features immediately
Comparison with Competitors
GLM-4.7 vs Other AI Coding Assistants
Key Advantages
- More cost-effective than GPT-4 and Claude
- Faster inference speed than larger models
- Better understanding of Asian programming patterns
- Superior Chinese language code documentation
- More transparent pricing model
- Lower latency for Asia-Pacific users
Unique Differentiators
- Optimized 7B architecture for efficiency
- Bilingual code generation (English/Chinese)
- Strong focus on software engineering principles
- Specialized training on modern frameworks
- Active development with frequent updates
Capturas de pantalla " Interface
Explore GLM-4.7's interface and capabilities:
GLM-4.7 provides an intuitive interface for code generation, debugging, and refactoring across 40+ programming languages with real-time suggestions and explanations.
Frequently Asked Questions
How does GLM-4.7 compare to GitHub Copilot?
GLM-4.7 offers comparable code generation quality at a more competitive price point. While Copilot has a larger ecosystem and IDE integration, GLM-4.7 excels in context understanding, bilingual support, and cost-effectiveness, especially for Asian markets.
What programming languages are supported?
GLM-4.7 supports 40+ programming languages including Python, JavaScript/TypeScript, Java, C++, Go, Rust, PHP, Ruby, Swift, Kotlin, and more. The model has particularly strong performance in web development languages and modern frameworks.
Can GLM-4.7 understand my existing codebase?
Yes! GLM-4.7 features a 128K token context window, allowing it to analyze and understand large codebases across multiple files. This enables context-aware suggestions that align with your existing code style and architecture.
Is my code data secure and private?
Zhipu AI implements strict data privacy measures. Your code is not used for model training unless you explicitly opt-in. All API communications are encrypted, and enterprise plans offer additional security features including on-premise deployment options.
How do I integrate GLM-4.7 into my workflow?
GLM-4.7 offers a RESTful API that can be integrated into any development environment. Official SDKs are available for Python, JavaScript, and Java. Community plugins exist for popular IDEs like VS Code, JetBrains IDEs, and Vim.
What kind of support is available?
Free tier users have access to community forums and documentation. Professional plan subscribers receive email support with 48-hour response time. Enterprise customers get dedicated technical account managers, priority support, and SLA guarantees.
Can GLM-4.7 help with code reviews?
Absolutely! GLM-4.7 excels at code review tasks, identifying potential bugs, security vulnerabilities, performance issues, and style inconsistencies. It provides detailed explanations and concrete suggestions for improvements aligned with best practices.
How often is the model updated?
Zhipu AI regularly updates GLM-4.7 with improvements, bug fixes, and expanded capabilities. Major version updates occur quarterly, with minor updates and optimizations released monthly. All updates are backward compatible with existing API integrations.
Final Verdict
GLM-4.7 is an impressive AI coding assistant that delivers exceptional value for developers. With its powerful 7B parameter architecture, broad language support, and competitive pricing, it stands as a compelling alternative to established competitors. Highly recommended for individual developers and teams looking for an intelligent, cost-effective coding companion.