AReaL
★ 5.9k
vs
E2B
★ 14.5k
AReaL vs E2B
AReaL: AReaL is a fully asynchronous reinforcement learning system from Tsinghua IIIS and Ant Group for training large reasoning and agentic models. Version 2.0 splits it into training, inference, agent and weight-update microservices, and black-box agent apps can be trained online by pointing their base_url at AReaL.; E2B: E2B is an open-source infrastructure that enables running AI-generated code securely in isolated cloud sandboxes. It provides JavaScript and Python SDKs to start and control these sandboxes for AI applications.
01
TL;DR
AReaLLLM Infra · ★ 5.9k
RL fine-tuning of reasoning models on math and coding tasks
E2BLLM Infra · ★ 14.5k
Executing code generated by large language models (LLMs)
02
Side-by-Side Comparison
Field
AReaLE2BCategory
LLM Infra
LLM Infra
Stars
★ 5.9k
★ 14.5k
License
Apache-2.0
Apache-2.0
Install Command
git clone https://github.com/areal-project/AReaL && cd AReaL && pip install uv && uv sync --extra cuda
pip install e2b
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
agent, agent-framework, llm
AI Code Generation, Sandboxing, SDK
03
Features
AReaL01Fully asynchronous RL training, reported 2.77x faster than synchronous systems in v0.3
02Online RL for black-box agents by replacing base_url and api_key
03Microservice architecture in 2.0 with separate training, inference, agent and weight-update services
04SGLang or vLLM inference backends, Ray clusters and Ascend NPU support
05Examples for math, SWE, search agents, tau2-bench and OpenClaw agents
E2B01Open-source infrastructure for AI code execution
02Secure isolated cloud sandboxes
03Execute AI-generated code safely
04Available with JavaScript and Python SDKs
05Self-hosting capabilities on major cloud providers
04
Use Cases
AReaL↳RL fine-tuning of reasoning models on math and coding tasks
↳Training multi-turn agents such as search or customer-service agents
↳Continuously improving an existing agent app via online RL
E2B↳Executing code generated by large language models (LLMs)
↳Integrating secure code execution into AI applications
↳Developing AI agents that require isolated runtime environments
05
Best For
AReaLEssentialTrending
E2BMost PopularEssentialTrending
FAQ
FAQ
What is the difference between AReaL and E2B?
Both AReaL and E2B are in the LLM Infra category. AReaL has 5.9k stars, while E2B has 14.5k stars.
Which is better, AReaL or E2B?
The best choice depends on your use case. Choose AReaL if RL fine-tuning of reasoning models on math and coding tasks, and E2B if Executing code generated by large language models (LLMs).
Is AReaL free or open source?
Yes, AReaL is open source on GitHub (Apache-2.0).
Is E2B free or open source?
Yes, E2B is open source on GitHub (Apache-2.0).
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