Cline Overview
Cline is an open-source, standalone tool designed for comprehensive compatibility across Windows, macOS, and Linux platforms. It supports leading LLMs such as GPT-5, Claude 4.5, Gemini 3.0, and Ollama, offering a substantial context window of 200k tokens for advanced natural language processing tasks. Cline provides local inference capabilities, enabling high-performance data processing without reliance on cloud infrastructure. This ensures enhanced privacy and control over data handling. Additionally, Cline allows for agentic editing across multiple files and offers full terminal access. The tool is freely available, making it an accessible choice for developers and researchers alike. Cline’s configuration is straightforward with a seamless migration process, guided by the .clinerc file.
Pros
- ✓ Open-source and free of charge.
- ✓ Supports a wide range of operating systems.
- ✓ Allows local inference for enhanced data privacy.
- ✓ Facilitates multi-file agentic editing.
- ✓ Seamless migration process.
Cons
- ✕ Limited context window compared to some cloud-based alternatives.
- ✕ Lacks predictive editing capabilities.
Devin Overview
Devin operates within a cloud architecture, providing robust support for both existing and emerging LLMs, including GPT-6, GPT-5, Claude 4.5, and Gemini 3.0. The tool is enhanced by its proprietary Devin-Planner custom model, which, along with a vast context window exceeding 10 million tokens, ensures powerful and scalable performance for complex processing tasks. Devin offers predictive editing and full terminal access, making it a highly efficient tool for developers seeking advanced editing features. While it lacks local inference, its cloud-based design allows for seamless scalability. The setup process requires some initial configuration, as guided by the .devinrc file, and pricing details are available upon contacting sales.
Pros
- ✓ Supports a vast context window exceeding 10 million tokens.
- ✓ Includes predictive editing capabilities.
- ✓ Cloud-based architecture for scalability.
- ✓ Proprietary custom model enhances functionality.
Cons
- ✕ No local inference capability.
- ✕ Requires setup for migration.
- ✕ No free tier; pricing details require contact with sales.
Comparison Table
| Feature | Cline | Devin |
|---|---|---|
| Architecture Type | standalone | cloud |
| Supported Os | Windows, macOS, Linux | Windows, macOS, Linux |
| Developer | Cline (open-source) | Devin |
| Supported Llms | GPT-5, Claude 4.5, Gemini 3.0, Ollama | GPT-6, GPT-5, Claude 4.5, Gemini 3.0 |
| Custom Model | – | Devin-Planner |
| Context Window | 200k tokens | 10M+ tokens |
| Agentic Editing | Yes, multi-file | Yes, multi-file |
| Terminal Access | Full | Full |
| Privacy Mode | Standard Privacy Policy | Standard Privacy Policy |
| Certifications | SOC2 Type II (Enterprise) | SOC2 Type II (Enterprise) |
| About Price | Free | Contact Sales |
| Config File | .clinerc | .devinrc |
| Migration | Seamless | Requires setup |
Conclusion
In conclusion, Cline and Devin cater to different user needs within the realm of technical tools. Cline’s open-source nature and local inference capabilities make it a great choice for those prioritizing privacy and cost-effectiveness. Devin, on the other hand, provides powerful cloud-based features and extensive context capabilities, ideal for users needing scalability and advanced processing power. Choosing between them depends on specific project requirements and budget considerations.