GPT Runner vs omp

Side-by-side comparison of two AI agent tools

Short answer

  • GPT Runner has had no commit in 37 months; omp is actively maintained (14,033 commits in the last 90 days).
  • omp is growing faster: +2,860 GitHub stars in the last 30 days vs +1 for GPT Runner.
  • Pick GPT Runner for: conversations with your files. Pick omp for: ⌥ Coding agent with the IDE wired in.

From GitHub data refreshed daily.

GPT Runneropen-source

Conversations with your files! Manage and run your AI presets!

o
ompopen-source

⌥ Coding agent with the IDE wired in. Built by Stencil Labs.

Metrics

GPT Runneromp
Stars38334.2k
Star velocity /mo0.78947368421052632.9k
Commits (90d)014.0k
Releases (6m)010
Overall score0.15088896796634120.9294757830416892

Pros

  • +Multi-platform availability with CLI, web, and VSCode extension options for flexible integration
  • +AI preset management system enables reusable, standardized AI configurations across projects and teams
  • +Direct code file conversation capability allows contextual AI assistance with existing codebases

    Cons

    • -Requires setup and configuration of AI presets before optimal use, adding initial complexity
    • -Dependent on external AI services which may have usage limits or costs
    • -Learning curve for effectively creating and managing AI presets for different use cases

      Use Cases

      • •Code review assistance where AI presets help analyze code quality and suggest improvements
      • •Development workflow automation using custom presets for repetitive coding tasks and documentation
      • •Team collaboration enhancement by sharing standardized AI configurations across development teams
        View GPT Runner DetailsView omp Details

        FAQ

        Which is more popular, GPT Runner or omp?
        omp has more GitHub stars (34,159 vs 383).
        Which is more actively developed, GPT Runner or omp?
        omp had more commits in the last 90 days (14,033 vs 0).
        Should I use GPT Runner or omp?
        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.