Claude Code vs. Gemini CLI vs. Cursor vs. Qwen Code

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The AI coding assistant market got messy fast. There have been so many players: Claude Code, Gemini CLI, Cursor, and now the recently released Qwen Code. From a user perspective, the more players, the more options, the better.

But with different pricing models, feature sets, and philosophies, choosing the right tool has become a headache. After extensive research and community feedback from developers using these tools in production, here’s what you need to know to make the right choice.

BTW, at the end of this post, I will also share an open source project: Code Context, an open-source MCP plugin that adds semantic code search to all these coding assistants, giving them deep context from your entire codebase.

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Claude Code is a terminal-native AI agent that embeds Claude 3.7 Sonnet directly into your command line. It operates as an agentic tool that can understand entire codebases, execute commands, and make coordinated changes across multiple files. The tool uses an incremental permission system, asking for approval at each step rather than making autonomous changes.

Gemini CLI brings Google’s Gemini 2.5 Pro to the command line as a fully open-source tool under Apache 2.0 license. It’s designed as a versatile local utility that integrates with Google Search and supports the Model Context Protocol (MCP) for extensibility. The tool can handle everything from coding to content generation and research.

Cursor is an AI-powered code editor built as a fork of VS Code. It integrates AI capabilities directly into the editing experience, providing real-time suggestions, autocomplete, and multi-file editing capabilities. The tool combines traditional IDE features with advanced AI through both quick completions and an Agent mode for complex tasks.

Qwen Code is a latest released command-line AI workflow tool built on the Qwen3-Coder-480B Mixture-of-Experts model. Adapted from Gemini CLI, it features enhanced parser support specifically optimized for Qwen models and can be integrated with other platforms like Claude Code and Cline.

Claude Code operates on a subscription model with pay-per-use characteristics. The Pro plan costs $20/month while the Max plan reaches $100/month. Real-world usage can get expensive quickly, with developers reporting costs around $8 for 90 minutes of intensive work. The pay-per-use nature means costs can be unpredictable for heavy users.

Gemini CLI offers the most generous free tier in the market. Users get 60 model requests per minute and 1,000 requests per day at no charge when using a personal Google account with a free Gemini Code Assist license. For professional usage, developers can upgrade to usage-based billing through Google AI Studio or Vertex AI.

Cursor uses a straightforward subscription model at $20/month for Pro features, which includes 500 premium model requests. This provides predictable monthly costs and makes budgeting easier for teams. The fixed pricing structure appeals to developers who want to avoid usage-based billing surprises.

Qwen Code costs depend entirely on your deployment choice. As an open-source model, you can self-host or use it through DashScope API. This flexibility potentially offers the lowest cost for high-volume usage, especially for organizations that can efficiently manage their own infrastructure.

Claude Code leverages Claude 3.7 Sonnet’s context capabilities, though specific limits aren’t publicly detailed. In practice, developers report it can handle massive codebases and files, with successful operations on 18,000+ line files that other tools failed to process.

Gemini CLI provides access to Gemini 2.5 Pro’s massive 1 million token context window. This enormous context capacity makes it excellent for understanding large codebases and handling complex, multi-file operations without losing track of dependencies and relationships.

Cursor uses a mix of purpose-built and frontier models with varying context windows depending on the specific model being used. The tool is optimized for typical development workflows and handles most coding projects effectively, though it may not match the extreme context capabilities of some competitors.

Qwen Code supports 256K tokens natively and can be extended up to 1M tokens using extrapolation methods like YaRN. This large context window is specifically optimized for repository-scale operations and dynamic data like pull requests, making it well-suited for agentic coding tasks.

Claude Code excels at deep codebase understanding, complex debugging, and systematic problem-solving. It can read terminal logs, understand linting errors, run CLI commands, and handle entire GitHub workflows from issue analysis to PR submission. The tool integrates with test suites and build systems while maintaining strong version control integration.

Gemini CLI combines coding capabilities with broader utility functions. It can ground prompts with Google Search, supports MCP for extensibility, allows custom prompts and instructions, and can be automated through scripting. The tool handles both development tasks and general research, making it versatile beyond pure coding.

Cursor provides sophisticated autocomplete that often predicts developer intent, multi-file editing capabilities through Agent mode, and seamless integration with existing VS Code workflows. Features include diff previews, versioned checkpoints, integrated terminal, and Bug Bot for AI-powered code review during development.

Qwen Code offers strong agentic coding capabilities with enhanced parser support for Qwen models. It can handle code understanding, editing large codebases, workflow automation, and complex operational tasks like handling pull requests and rebases. The tool achieves 37.5% accuracy on agentic coding benchmarks.

Claude Code consistently produces higher-quality code requiring fewer iterations. Developers report superior debugging capabilities and better handling of complex architectural decisions. It can successfully work with massive files and codebases that challenge other tools, though it operates more slowly due to its permission-based approach.

Gemini CLI delivers solid performance with the advantage of Google Search integration for real-time information access. The large context window enables handling of complex projects, though it may not match Claude Code’s reasoning depth for sophisticated debugging scenarios.

Cursor provides the fastest user experience for routine coding tasks. Its tab-complete functionality is exceptionally responsive, often feeling predictive rather than reactive. Agent mode can handle complex refactoring effectively, though it sometimes suggests unnecessary changes or tries to accomplish too much in a single iteration.

Qwen Code demonstrates strong performance on agentic coding tasks, with benchmark results showing competitive accuracy. The tool benefits from being specifically optimized for coding workflows, though real-world performance can vary depending on infrastructure and configuration choices.

Claude Code integrates well with existing development tools and workflows, particularly version control systems and CI/CD pipelines. Being developed by Anthropic, it receives regular updates and improvements, though the community around it is smaller compared to open-source alternatives.

Gemini CLI benefits from being fully open-source with active community contribution encouraged. It supports emerging standards like MCP and can be extended through plugins. The Google backing provides stability, while the Apache 2.0 license enables community-driven development and transparency.

Cursor has built a strong community of developers, particularly those migrating from VS Code. The tool maintains compatibility with VS Code extensions, themes, and keybindings, making adoption seamless. Regular feature updates and responsive development have created positive momentum in the developer community.

Qwen Code leverages the broader open-source AI community and integrates with multiple platforms including Claude Code and Cline. As part of the Qwen ecosystem, it benefits from ongoing model improvements and community contributions, though the ecosystem is still developing compared to more established tools.

Claude Code requires comfort with terminal-based workflows, which can be a barrier for some developers. However, once familiar with the interface, many find the conversational approach intuitive. The permission-based system adds friction but builds trust and understanding of what the tool is doing.

Gemini CLI offers straightforward command-line usage with simple installation through npm. The interface is clean and the extensive free tier allows for experimentation without cost concerns. Being terminal-based, it requires similar comfort levels as Claude Code.

Cursor provides the most accessible experience for developers familiar with VS Code. The migration process is seamless, importing existing configurations in one click. The GUI-based approach with visual feedback makes it immediately familiar to most developers, reducing the learning curve significantly.

Qwen Code requires more technical setup and configuration compared to commercial alternatives. While this provides flexibility, it also means a steeper learning curve and more initial investment in setup and configuration. Documentation is still developing as the project matures.

Claude Code offers enterprise-grade security but processes code through Anthropic’s servers. While Anthropic has strong security practices, sensitive codebases may require careful consideration of what information is shared with external services.

Gemini CLI being open-source allows for security auditing, though it typically processes requests through Google’s servers. The transparency of the codebase enables security review, but data handling follows Google’s privacy policies for API usage.

Cursor provides SOC 2 certification and offers Privacy Mode where code is never stored remotely without explicit consent. This addresses major privacy concerns while maintaining the benefits of cloud-based AI processing. The privacy controls are granular and developer-friendly.

Qwen Code offers the most control over security and privacy since it can be completely self-hosted. Organizations can run the model on their own infrastructure, ensuring sensitive code never leaves their environment. This makes it attractive for companies with strict security requirements.

• Choose Claude Code when working on complex, large codebases where debugging and code quality are critical. It’s ideal for professional development teams that can justify the premium cost through improved code quality and reduced debugging time. Best for developers comfortable with terminal workflows who need sophisticated reasoning capabilities.
• Choose Gemini CLI when starting with AI coding tools, thanks to its generous free tier, or when work involves frequent research and documentation lookup. It’s excellent for learning new frameworks, working across multiple environments, and for developers who value open-source transparency and community-driven development.
• Choose Cursor for developers prioritizing speed, rapid prototyping, and a polished IDE experience. It’s perfect for teams migrating from VS Code who want immediate productivity gains with minimal learning curve. Ideal for day-to-day coding tasks, quick iterations, and developers who prefer GUI-based workflows.
• Choose Qwen Code when you need cutting-edge open-source AI with maximum customization control. It’s best for organizations building internal developer tools, teams with specific security requirements, or those who want complete control over their AI coding infrastructure while potentially achieving the lowest long-term costs.

While these coding tools are powerful, they all have a code search problem. They can’t search context properly. Claude still uses outdated grep. Cursor uses very simple vector search. Their context retrieval? Honestly, pretty mediocre. Gemini CLI and Qwen Code, the same.

So, to understand your codebase and retrieve the right code snippet for your needs, your coding assistant needs to understand and search the context first. Code Context is one of the solutions to this problem.

Code Context is an open-source, MCP-compatible plugin that transforms any AI coding agent into a context-aware powerhouse. It’s like giving your AI assistant the institutional memory of a senior developer who’s worked on your codebase for years. Whether you’re using Qwen Code, Claude Code, Gemini CLI, working in VSCode, or even coding in Chrome, Code Context brings semantic code search to your workflow.

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• Semantic Code Search via Natural Language
• Multi-Language Support: Search seamlessly across 15+ programming languages, including JavaScript, Python, Java, and Go, with consistent semantic understanding across them all.
• AST-Based Code Chunking: Code is automatically split into logical units, such as functions and classes, using AST parsing, ensuring search results are complete, meaningful, and never cut off mid-function.
• Live, Incremental Indexing: Code changes are indexed in real time. As you edit files, the search index stays up to date — no need for manual refreshes or re-indexing.
• Fully Local, Secure Deployment: Run everything on your own infrastructure. Code Context supports local models via Ollama and indexing via Milvus, so your code never leaves your environment.
• First-Class IDE Integration: The VSCode extension lets you search and jump to results instantly — right from your editor, with zero context switching.
• MCP Protocol Support: Code Context speaks MCP, making it easy to integrate with AI coding assistants and bring semantic search directly into their workflows.
• Browser Plugin Support: Search repositories directly from GitHub in your browser — no tabs, no copy-pasting, just instant context wherever you’re working.

Check its Github repo here and give it a try. Feel free to share with us your feedback.

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