Home Projects Baichuan2
Baichuan2
Python

Baichuan2

A series of large language models developed by Baichuan Intelligent Technology

by baichuan-inc · GitHub
Stars
Forks
License
Created
Last commit
Language
Likely
Self-hostable
artificial-intelligencebenchmarkcevalApache-2.0PythonSelf-hostable
View on GitHub
In plain words

Interact with advanced AI models for various tasks and questions.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
Baichuan2 — GitHub preview card
📈 Star history
4.09k4.08k
2026-07-072026-08-31
📈 Track Baichuan2

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

A series of large language models developed by Baichuan Intelligent Technology

Baichuan2 has 4.1k stars on GitHub. It has been forked 294 times. Baichuan2 is written mainly in Python. It has been in active development since 2023. Baichuan2 is available under the Apache-2.0 license. Its main topics are artificial-intelligence, benchmark, ceval, chatgpt.

Frequently asked questions

What is Baichuan2?

A series of large language models developed by Baichuan Intelligent Technology

Is Baichuan2 open source?

Baichuan2 is an open-source project. It is released under the Apache-2.0 license.

Is Baichuan2 free?

Yes. Baichuan2 is free and open source — you can use, modify and self-host it.

What license does Baichuan2 use?

Baichuan2 is available under the Apache-2.0 license.

What language is Baichuan2 written in?

Baichuan2 is written mainly in Python.

🏅 Maintainer of this project?
olud.ai badge — Baichuan2

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=baichuan-inc-baichuan2)](https://olud.ai/project/baichuan-inc-baichuan2.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.