Dev-GPT vs Devika
Side-by-side comparison of two AI agent tools
Short answer
- Devika is growing faster: +9 GitHub stars in the last 30 days vs +-0 for Dev-GPT.
- Pick Dev-GPT for: your Virtual Development Team. Pick Devika for: devika is the first open-source implementation of an Agentic Software Engineer.
From GitHub data refreshed daily.
Dev-GPTopen-source
Your Virtual Development Team
Devikaopen-source
Devika is the first open-source implementation of an Agentic Software Engineer. Initially started as an open-source alternative to Devin.
Metrics
| Dev-GPT | Devika | |
|---|---|---|
| Stars | 1.9k | 19.6k |
| Star velocity /mo | -0.3157894736842105 | 9.31578947368421 |
| Commits (90d) | 0 | 0 |
| Releases (6m) | 0 | 0 |
| Downloads (30d, npm + PyPI) | 70 | — |
| Overall score | 0.12310180580341948 | 0.18934512368151743 |
Pros
- +Multi-agent AI system with specialized roles (Product Manager, Developer, DevOps) provides comprehensive development coverage
- +Simple installation and CLI interface makes it accessible to developers of all skill levels
- +Cross-platform support and integration with popular APIs (OpenAI, Google) ensures broad compatibility
- +Multi-LLM support with flexibility to choose from commercial providers (Claude 3, GPT-4, Gemini) or run local models via Ollama
- +Comprehensive AI capabilities including planning, reasoning, web research, and multi-language code generation in a single platform
- +Open-source alternative to proprietary solutions like Devin, allowing community contributions and customization
Cons
- -Experimental version status indicates potential instability and incomplete features
- -Requires paid OpenAI API access, adding ongoing operational costs
- -Limited scope to microservice development only, not suitable for larger applications or different architectural patterns
- -Currently in early development/experimental stage with many unimplemented and broken features
- -Requires specific Python version constraints (>= 3.10 and < 3.12) which may limit compatibility
- -Performance heavily dependent on chosen LLM provider, with optimal results requiring paid commercial models
Use Cases
- •Rapid prototyping of microservices for MVP development and proof-of-concept projects
- •Solo developers or small teams lacking expertise in specific areas (DevOps, architecture) who need full-stack automation
- •Learning and experimentation with microservice architecture patterns through AI-generated examples
- •Creating new software features from high-level requirements with minimal human guidance
- •Debugging and fixing existing code issues through AI-powered analysis and solution generation
- •Developing entire projects from scratch by breaking down complex objectives into manageable coding tasks
FAQ
- Which is more popular, Dev-GPT or Devika?
- Devika has more GitHub stars (19,556 vs 1,866).
- Which is more actively developed, Dev-GPT or Devika?
- Dev-GPT had more commits in the last 90 days (0 vs 0).
- Should I use Dev-GPT or Devika?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.