Open Interpreter
★ 68.6k
vs
code-act
★ 1.7k
Open Interpreter vs code-act
Open Interpreter: Open Interpreter is a terminal coding agent optimized for low-cost and open models. It is a fork of OpenAI's Codex that can emulate other agent harnesses (such as Claude Code, Kimi Code or Qwen Code) to get the best results from each model, runs commands in native sandboxes on macOS, Linux and Windows, and works with ACP-compatible editors and the Codex SDK.; code-act: CodeAct unifies LLM agents' actions into an executable code space, enabling dynamic revision and new actions based on execution results. This approach significantly outperforms traditional text and JSON action methods, improving LLM agent success rates on complex tasks.
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TL;DR
Open InterpreterCode Assistant · ★ 68.6k
When to choose:
- You want a fast Rust-based terminal coding agent (Apache-2.0) that squeezes better results out of low-cost and open-weights models via harness emulation.
- You want native OS sandboxing (Seatbelt on macOS, Landlock+bubblewrap on Linux, AppContainer on Windows) and support for AGENTS.md, skills, and MCP.
When to skip:
- You are looking for the old Python `pip install open-interpreter` library from 2023–2024; the project has been completely rewritten as a Rust fork of Codex.
- You just want a free-tier official Gemini agent without configuring endpoints and harnesses; Gemini CLI is simpler.
code-actLLM Infra · ★ 1.7k
Developing Advanced LLM Agents: For researchers and developers aiming to build more capable and robust LLM agents that can interact dynamically with environments.
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Side-by-Side Comparison
Field
Open Interpretercode-actCategory
Code Assistant
LLM Infra
Stars
★ 68.6k
★ 1.7k
License
Apache-2.0
MIT
Install Command
curl -fsSL https://www.openinterpreter.com/install | sh
pip install -r requirements.txt
Updated
1w ago
2y ago
Open Source
Yes
Yes
Tags
LLM, Code Execution, AI Agent
LLM Agents, Code Execution, Instruction Tuning
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Features
Open Interpreter01Switch between emulated agent harnesses (native, Claude Code, Kimi Code, Qwen Code, SWE-agent and more) with /harness
02Native command sandboxing on macOS, Linux and Windows
03Switch providers and models from the TUI, including any OpenAI-compatible endpoint
04Runs as an Agent Client Protocol (ACP) agent for editors and as a drop-in for the Codex SDK
05Supports MCP, skills, hooks, permissions and shared AGENTS.md instructions
code-act01Unified Action Space via Executable Code: Consolidates LLM agents' actions into a unified, executable code space.
02Dynamic Action Revision: Allows LLM agents to dynamically revise prior actions or emit new actions based on real-time observations.
03Integrated Python Interpreter: Seamlessly integrates with a Python interpreter for code execution.
04Superior Performance: Outperforms widely used alternatives like Text and JSON in LLM agent success rates (up to 20% higher).
05Instruction-Tuned Agents (CodeActAgent): Provides pre-trained CodeActAgent models (Mistral, Llama-2) that excel in out-of-domain agent tasks.
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Use Cases
Open Interpreter↳Getting strong coding-agent results from inexpensive or open models such as Kimi, GLM, Qwen or DeepSeek
↳Using one terminal agent across several model providers without changing tools
↳Testing web and native apps with the built-in QA skill
code-act↳Developing Advanced LLM Agents: For researchers and developers aiming to build more capable and robust LLM agents that can interact dynamically with environments.
↳Automated Code Execution and Problem Solving: For scenarios requiring LLMs to execute code, debug, and iterate on solutions based on execution feedback.
↳Complex Task Automation: For automating multi-turn, complex tasks that benefit from dynamic action revision and tool use.
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Best For
Open InterpreterMost PopularEssentialTrending
code-act—
FAQ
FAQ
What is the difference between Open Interpreter and code-act?
Both Open Interpreter and code-act are in the Code Assistant category. Open Interpreter has 68.6k stars, while code-act has 1.7k stars.
Which is better, Open Interpreter or code-act?
The best choice depends on your use case. Choose Open Interpreter if Getting strong coding-agent results from inexpensive or open models such as Kimi, GLM, Qwen or DeepSeek, and code-act if Developing Advanced LLM Agents: For researchers and developers aiming to build more capable and robust LLM agents that can interact dynamically with environments..
Is Open Interpreter free or open source?
Yes, Open Interpreter is open source on GitHub (Apache-2.0).
Is code-act free or open source?
Yes, code-act is open source on GitHub (MIT).
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