agenticSeek vs Devika

Side-by-side comparison of two AI agent tools

a
agenticSeekopen-source

Fully Local Manus AI. No APIs, No $200 monthly bills. Enjoy an autonomous agent that thinks, browses the web, and code for the sole cost of electricity.

Devikaopen-source

Devika is the first open-source implementation of an Agentic Software Engineer. Initially started as an open-source alternative to Devin.

Metrics

agenticSeekDevika
Stars27.4k19.6k
Star velocity /mo2.3k9.46524064171123
Commits (90d)480
Releases (6m)00
Overall score0.63198621403433750.1985048272860232

Pros

    • +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

      • -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

        • •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
        View agenticSeek DetailsView Devika Details

        FAQ

        Which is more popular, agenticSeek or Devika?
        agenticSeek has more GitHub stars (27,396 vs 19,556).
        Which is more actively developed, agenticSeek or Devika?
        agenticSeek had more commits in the last 90 days (48 vs 0).
        Should I use agenticSeek 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.