AgentIndex icon
AgentIndex
AReaL logo
AReaL
★ 5.9k
vs
inno-agent logo
inno-agent
★ 1.3k

AReaL vs inno-agent

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.; inno-agent: Inno Agent is a personal learning agent built on the Pi coding-agent SDK without modifying its kernel. It organizes learning support into three memory layers (learner profile, native wiki, cross-session recall) and adds a cron scheduler, Feishu/WeChat channels and a Practice Lab, shipped as desktop app, web UI and CLI.

01

TL;DR

AReaL logo
AReaLLLM Infra · ★ 5.9k

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

Read AReaL full review →
inno-agent logo
inno-agentMemory & Context · ★ 1.3k

Personal tutor that tracks goals and misconceptions over time

Read inno-agent full review →
02

Side-by-Side Comparison

Field
AReaL logoAReaL
inno-agent logoinno-agent
Category
LLM Infra
Memory & Context
Stars
★ 5.9k
★ 1.3k
License
Apache-2.0
MIT
Install Command
git clone https://github.com/areal-project/AReaL && cd AReaL && pip install uv && uv sync --extra cuda
git clone https://github.com/hhyqhh/inno-agent.git && cd inno-agent && npm install && npm run build
Updated
1d ago
2d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent, agent-framework, llm
agent-framework, cli, electron
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
inno-agent logoinno-agent
01L1 learner profile, L2 wiki with BM25 + knowledge-graph retrieval, L3 session recall on SQLite FTS5
02Natural-language cron jobs for proactive reminders
03Feishu and WeChat channels with a unified reminder dispatcher
04Practice Lab with an in-browser terminal whose run records the agent can read
05Any OpenAI- or Anthropic-compatible provider, including Ollama and DeepSeek
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
inno-agent logoinno-agent
↳Personal tutor that tracks goals and misconceptions over time
↳Building a personal wiki from PDFs and notes
↳Teachers preparing lesson plans and slides with presets
05

Best For

AReaL logoAReaL
EssentialTrending
inno-agent logoinno-agent
EssentialTrending
FAQ

FAQ

What is the difference between AReaL and inno-agent?
Both AReaL and inno-agent are in the LLM Infra category. AReaL has 5.9k stars, while inno-agent has 1.3k stars.
Which is better, AReaL or inno-agent?
The best choice depends on your use case. Choose AReaL if RL fine-tuning of reasoning models on math and coding tasks, and inno-agent if Personal tutor that tracks goals and misconceptions over time.
Is AReaL free or open source?
Yes, AReaL is open source on GitHub (Apache-2.0).
Is inno-agent free or open source?
Yes, inno-agent is open source on GitHub (MIT).
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Related

Alternatives to AReaL →Alternatives to inno-agent →AReaL details →inno-agent details →