AgentIndex icon
AgentIndex
AReaL logo
AReaL
★ 5.9k
vs
rllm logo
rllm
★ 5.9k

AReaL vs rllm

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.; rllm: rLLM is an open-source framework designed for post-training language agents using reinforcement learning. It allows users to easily build, train, and deploy custom agents and environments for real-world workloads.

01

TL;DR

AReaL logo
AReaLLLM Infra · ★ 5.9k

RL fine-tuning of reasoning models on math and coding tasks

Read AReaL full review →
rllm logo
rllmLLM Infra · ★ 5.9k

Training powerful coding models for tasks like code generation and bug fixing.

Read rllm full review →
02

Side-by-Side Comparison

Field
AReaL logoAReaL
rllm logorllm
Category
LLM Infra
LLM Infra
Stars
★ 5.9k
★ 5.9k
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
uv pip install "rllm[verl] @ git+https://github.com/rllm-org/rllm.git"
Updated
1d ago
1w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent, agent-framework, llm
Reinforcement Learning, Language Agents, LLM
03

Features

AReaL logoAReaL
01Fully 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
rllm logorllm
01Open-source framework for reinforcement learning-based post-training of language agents.
02Supports building, training, and deploying custom agents and environments.
03Offers multiple training backends including 'verl' and 'tinker'.
04Enables LoRA and VLM training for advanced models.
05Includes AgentWorkflowEngine for training over arbitrary agentic programs.
04

Use Cases

AReaL logoAReaL
↳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
rllm logorllm
↳Training powerful coding models for tasks like code generation and bug fixing.
↳Developing sophisticated software engineering agents for automated tasks.
↳Building and evaluating multi-agent systems using reinforcement learning techniques.
05

Best For

AReaL logoAReaL
EssentialTrending
rllm logorllm
Trending
FAQ

FAQ

What is the difference between AReaL and rllm?
Both AReaL and rllm are in the LLM Infra category. AReaL has 5.9k stars, while rllm has 5.9k stars.
Which is better, AReaL or rllm?
The best choice depends on your use case. Choose AReaL if RL fine-tuning of reasoning models on math and coding tasks, and rllm if Training powerful coding models for tasks like code generation and bug fixing..
Is AReaL free or open source?
Yes, AReaL is open source on GitHub (Apache-2.0).
Is rllm free or open source?
Yes, rllm is open source on GitHub (Apache-2.0).
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Related

Alternatives to AReaL →Alternatives to rllm →AReaL details →rllm details →