AgentIndex icon
AgentIndex
AReaL logo
AReaL
★ 5.9k
vs
Ornn logo
Ornn
★ 20

AReaL vs Ornn

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.; Ornn: Ornn is an agent-facing skill lifecycle API — the npm registry and CLI fused into one, but for AI agent skills. Agents call Ornn directly over HTTP or MCP to search, pull, install, execute, build, upload, and share skills. It is model-agnostic, working with Claude, GPT, Gemini, or any custom runtime. Designed for agentic-system builders who want to manage reusable skills programmatically rather than hardcoding capabilities into each agent.

01

TL;DR

AReaL logo
AReaLLLM Infra · ★ 5.9k

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

Read AReaL full review →
Ornn logo
OrnnDev Tooling · ★ 20

Building an agentic system where agents can discover and install new capabilities at runtime

Read Ornn full review →
02

Side-by-Side Comparison

Field
AReaL logoAReaL
Ornn logoOrnn
Category
LLM Infra
Dev Tooling
Stars
★ 5.9k
★ 20
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
git clone https://github.com/ChronoAIProject/Ornn.git
Updated
1d ago
3w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent, agent-framework, llm
agent, agent-framework, ai-agents
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
Ornn logoOrnn
01Full skill lifecycle: search, pull, install, execute, build, upload, share
02HTTP and MCP transport — agents call directly without human intermediation
03Model-agnostic: works with Claude, GPT, Gemini, or any custom runtime
04NyxID-based authentication for skill ownership and access control
05Web UI for skill owners and platform admins (secondary surface)
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
Ornn logoOrnn
↳Building an agentic system where agents can discover and install new capabilities at runtime
↳Publishing reusable agent skills for other developers to consume via API or MCP
↳Managing a library of agent skills that multiple AI apps share
05

Best For

AReaL logoAReaL
EssentialTrending
Ornn logoOrnn
—
FAQ

FAQ

What is the difference between AReaL and Ornn?
Both AReaL and Ornn are in the LLM Infra category. AReaL has 5.9k stars, while Ornn has 20 stars.
Which is better, AReaL or Ornn?
The best choice depends on your use case. Choose AReaL if RL fine-tuning of reasoning models on math and coding tasks, and Ornn if Building an agentic system where agents can discover and install new capabilities at runtime.
Is AReaL free or open source?
Yes, AReaL is open source on GitHub (Apache-2.0).
Is Ornn free or open source?
Yes, Ornn is open source on GitHub (Apache-2.0).
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Related

Alternatives to AReaL →Alternatives to Ornn →AReaL details →Ornn details →