GPT-Code vs omp

Side-by-side comparison of two AI agent tools

Short answer

  • GPT-Code has had no commit in 38 months; omp is actively maintained (13,995 commits in the last 90 days).
  • omp is growing faster: +3,030 GitHub stars in the last 30 days vs +-6 for GPT-Code.
  • Pick GPT-Code for: an open source implementation of OpenAI's ChatGPT Code interpreter. Pick omp for: ⌥ Coding agent with the IDE wired in.

From GitHub data refreshed daily.

GPT-Codeopen-source

An open source implementation of OpenAI's ChatGPT Code interpreter

o
ompopen-source

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

Metrics

GPT-Codeomp
Stars3.5k34.1k
Star velocity /mo-5.5555555555555553.0k
Commits (90d)014.0k
Releases (6m)010
Overall score0.113105381166257140.9384072578113428

Pros

  • +Simple installation via pip with one-command startup (pip install gpt-code-ui && gptcode)
  • +Full context awareness maintains conversation history and can reference previous code executions
  • +File upload/download support enables working with external data sources and exporting results

    Cons

    • -Limited to Python code execution only, cannot run other programming languages
    • -Requires OpenAI API key and incurs usage costs for each interaction
    • -No apparent built-in security isolation or sandboxing details mentioned for code execution safety

      Use Cases

      • •Data analysis and visualization projects where you need AI assistance to generate charts and insights
      • •Rapid prototyping and proof-of-concept development with AI-generated code snippets
      • •Educational scenarios for learning Python programming through AI-guided code generation
        View GPT-Code DetailsView omp Details

        FAQ

        Which is more popular, GPT-Code or omp?
        omp has more GitHub stars (34,075 vs 3,535).
        Which is more actively developed, GPT-Code or omp?
        omp had more commits in the last 90 days (13,995 vs 0).
        Should I use GPT-Code 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.