8 Best e2b Alternatives in 2026 (Open Source)
e2b — Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app . Purpose-built cloud infrastructure for AI-generated code execution — secure sandboxes designed specifically for LLM output, not repurposed containers
Short answer
- Closest match to e2b: E2B.
- Most actively developed: Open Interpreter (2,737 commits in the last 90 days).
- Fastest growing: Open Interpreter (+887 GitHub stars in the last 30 days).
- No commit in 6+ months: Code Interpreter API, AgentRun, TaskWeaver and Instrukt and 1 more.
These 8 open-source tools do the same job. They are ordered by how closely they match e2b, with live GitHub data so you can see which projects are actively maintained.
By package downloads E2B is the most used here (12.9M in the last 30 days), even though Open Interpreter has the most GitHub stars. See all agent tools by downloads.
| Tool | GitHub stars | Stars / 30d | Last commit | Downloads / 30d |
|---|---|---|---|---|
| e2b(original) | 2.4k | +25 | 2026-09-30 | — |
| E2B | 14.1k | +420 | 2026-10-02 | 12.9M |
| Code Interpreter API | 3.8k | -2 | 2024-11-07 | 192 |
| Open Interpreter | 68.5k | +887 | 2026-10-02 | — |
| AgentRun | 380 | +2 | 2024-11-10 | — |
| smolagents | 29.7k | +531 | 2026-09-30 | — |
| TaskWeaver | 6.2k | +6 | 2026-03-23 | — |
| Instrukt | 329 | 0 | 2025-05-14 | 12 |
| CodeAct | 1.7k | +11 | 2024-05-23 | — |
1. E2B
Open-source, secure environment with real-world tools for enterprise-grade agents.
What sets it apart: Purpose-built sandboxed execution for AI-generated code with sub-second startup — vs generic containers which require more setup and have slower cold starts
Best for: Running untrusted AI-generated code safely; Building code execution features into AI applications
2. Code Interpreter API
👾 Open source implementation of the ChatGPT Code Interpreter
What sets it apart: vs raw LangChain code execution: sandboxed Code Interpreter replica with file I/O and conversation memory — the closest open-source implementation of ChatGPT's Code Interpreter feature
Best for: Developers wanting open-source ChatGPT Code Interpreter functionality; Data analysis automation with file input/output; Building code execution agents with sandboxed safety
3. Open Interpreter
A natural language interface for computers
What sets it apart: vs ChatGPT Code Interpreter: runs locally with full internet access, no file size limits, any package available, and persistent state
Best for: Power users wanting natural language control of their computer; Rapid prototyping and data analysis via conversational coding
4. AgentRun
The easiest, and fastest way to run AI-generated Python code safely
What sets it apart: Single-line safe Python code execution from LLMs in Docker containers with automatic dependency management, safety checks, and resource limiting
Best for: safe-llm-code-execution; sandboxed-python-runtime; giving-code-execution-to-llm-agents
5. smolagents
🤗 smolagents: a barebones library for agents that think in code.
What sets it apart: vs LangChain: code-first agent design uses 30% fewer tokens by writing Python instead of JSON tool calls; vs CrewAI: lighter ~1000 lines core with HuggingFace Hub integration for sharing agents/tools
Best for: Building code-writing AI agents with sandboxed execution; HuggingFace ecosystem users wanting agent capabilities; Multi-modal agent applications
6. TaskWeaver
The first "code-first" agent framework for seamlessly planning and executing data analytics tasks.
What sets it apart: Unlike text-only agent frameworks like AutoGen, TaskWeaver preserves full code execution state and in-memory data across turns, enabling seamless multi-step data analytics that manipulate DataFrames and complex structures directly
Best for: Data scientists needing automated multi-step analytics pipelines with code generation; Teams building AI agents that must handle complex data structures like DataFrames natively
7. Instrukt
Integrated AI environment in the terminal. Build, test and instruct agents.
What sets it apart: vs LangChain CLI / Open Interpreter: terminal-native TUI with Docker sandboxing, modular agent packages, and language-aware code indexing — designed for headless servers and SSH workflows
Best for: Terminal-native code analysis and documentation Q&A via RAG; Developers wanting secure sandboxed AI agent execution; SSH/headless server environments needing AI tooling
8. CodeAct
Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji.
What sets it apart: vs ReAct/text-based agents: executable Python code as unified action space with containerized execution, achieving 20% higher success rate than JSON/text actions
Best for: Research on code-based agent action spaces; Building agents that execute Python code as their primary action mechanism
FAQ
- What are the best alternatives to e2b?
- The closest open-source alternatives to e2b are E2B, Code Interpreter API and Open Interpreter, followed by AgentRun, smolagents and TaskWeaver. They are ranked by how closely they match what e2b does.
- Which e2b alternative is the most popular?
- Open Interpreter has the most GitHub stars among e2b alternatives, with 68,497 stars.
- Which e2b alternative is the most actively maintained?
- By recent activity, Open Interpreter (2,737 commits in the last 90 days) is the most actively developed alternative.
Maintain e2b or one of these alternatives?
Each tool page has a maintainer box: a README badge with your live rank and stars, or a homepage feature for $49 / 7 days.
e2b · E2B · Code Interpreter API · Open Interpreter · AgentRun · smolagents