Which is more popular, GPT-Code or Open Interpreter?

Open Interpreter has more GitHub stars (68,485 vs 3,535).

Which is more actively developed, GPT-Code or Open Interpreter?

Open Interpreter had more commits in the last 90 days (2,738 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

GPT-Code has had no commit in 38 months; Open Interpreter is actively maintained (2,738 commits in the last 90 days).
Open Interpreter is growing faster: +890 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 Open Interpreter for: a natural language interface for computers.

From GitHub data refreshed daily.

GPT-Codeopen-source

An open source implementation of OpenAI's ChatGPT Code interpreter

A natural language interface for computers

+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

+Natural language interface for complex computer tasks with multi-language code execution support
+Local execution ensures data privacy and eliminates cloud dependencies while providing full system access
+Built-in safety measures with user approval prompts prevent unauthorized code execution

-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

-Requires manual approval for each code execution which can slow down automated workflows
-Local setup and dependencies may be complex for users unfamiliar with Python environments
-Potential security risks from code execution despite approval prompts, especially for inexperienced users

•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

•Data analysis and visualization tasks like plotting stock prices and cleaning large datasets
•Media manipulation including creating and editing photos, videos, and PDF documents
•Browser automation for web research and data collection tasks

Which is more popular, GPT-Code or Open Interpreter?: Open Interpreter has more GitHub stars (68,485 vs 3,535).
Which is more actively developed, GPT-Code or Open Interpreter?: Open Interpreter had more commits in the last 90 days (2,738 vs 0).
Should I use GPT-Code or Open Interpreter?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.