AReaL
Reinforcement learning system for training LLM-based agents.
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Use cases
About AReaL
AReaL is listed in our frameworks category and is aimed at builders. Reinforcement learning system for training LLM-based agents. Pricing, as the maker states it: Open source. Maturity: Mature. We last checked the official link on 2026-10-16.
What is AReaL?
AReaL is a large-scale asynchronous reinforcement-learning system for training LLM-based agents, originally developed by Tsinghua IIIS and the AReaL team at Ant Group.
It is built on a fully asynchronous RL training paradigm optimized for efficiency and scalability.
Sources: the official README and our directory listing, checked 2026-10-18. Official site: areal-ai.io.
Who is AReaL for?
ML researchers and engineers training agentic models with RL at scale.
AReaL at a glance
- Open source: Yes (Apache License 2.0)
- GitHub: areal-project/AReaL · 5,863 stars (as of Oct 21, 2026)
Key features
- Fully asynchronous RL training
- Built for large-scale agent training
- Open source
AReaL FAQ
What is AReaL?
AReaL is a large-scale asynchronous reinforcement-learning system for training LLM-based agents, originally developed by Tsinghua IIIS and the AReaL team at Ant Group.
Who is AReaL for?
ML researchers and engineers training agentic models with RL at scale.
Is AReaL free?
AReaL's pricing, as the maker states it: Open source. Open-source tools are free to use, though you may still pay for model API usage or a hosted plan. Check the official site for current plans.
Is AReaL open source?
Yes. AReaL is released under the Apache License 2.0, according to its GitHub repository.
What are alternatives to AReaL?
Similar tools include OpenFang, OpenPipe, RAGEN, AIOS, Agent Lightning and Lagent.
AReaL ratings and reviews
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AReaL alternatives
Other frameworks tools in our directory. See all frameworks tools →
OpenFang
Open-source agent operating system for running autonomous agents.
OpenPipe
Reinforcement learning tooling, including the ART library, to train better agents.
RAGEN
Reinforcement learning framework for multi-turn LLM agents.
AIOS
Research AI agent operating system that handles scheduling, context switching, memory, storage and tool management for LLM-based agents.
Agent Lightning
Microsoft's lightweight trainer that improves existing agents with reinforcement learning through a model proxy, without rewriting the agent's tools or control flow.
Lagent
Lightweight PyTorch-inspired framework from InternLM for building LLM-based agents.
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