Beyond the Hype: Choosing the Right Model for Your Daily Workflow

Short summary

Author tested Claude, Gemini, and ChatGPT for code generation and found Claude unmatched for context analysis and code quality despite high token consumption (~$200/month); ChatGPT offers optimal token efficiency; Gemini has poor code generation. Spec-kit context injection enforces coding standards, enabling models to generate drop-in-ready code across all platforms.

• •Claude excels at code generation and context analysis but consumes tokens heavily (~$200/month); ChatGPT provides best token efficiency; Gemini has poor code generation capability
• •Spec-kit context injection enforces coding standards and practices, enabling models to generate drop-in-ready code without manual optimization
• •MCP integration (Jira, Confluence) automates context gathering but increases token usage significantly

Generated with AI, which can make mistakes.