Learn how AgentOS and LobeChat differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai agent platforms is best for you.
Last 30 days
Last commit
8 hours agoRepository age
1 yearVersion
v0.15.27License
Apache-2.0Repository
framersai/agentos
Last 30 days
Last commit
6 hours agoRepository age
3 yearsVersion
v2.2.20Self-hosted
YesRepository
lobehub/lobehub
Both AgentOS and LobeChat have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
LobeChat significantly outpaces AgentOS in community adoption with 83,533 stars compared to 683 stars on GitHub. This 122.3x difference suggests LobeChat has a much larger and more active community. In terms of developer contributions, LobeChat has 16,006 forks, indicating strong developer engagement.
AgentOS is growing faster, adding 10 stars in the last 30 days (+1.5%) against adding 676 stars for LobeChat (+0.8%). AgentOS is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with AgentOS last updated 8 hours ago and LobeChat 6 hours ago.
Both tools share common technology foundations, being built with JavaScript, Typescript. However, they differ in their additional technology choices: LobeChat leverages CSS, Bash, JSX, Next.js.
LobeChat has been in development longer, starting 3 years ago, compared to AgentOS which began 1 year ago. This 2.5-year head start suggests LobeChat may have more mature features and established processes.
AgentOS is licensed under Apache-2.0, while LobeChat's license terms are not publicly specified.
Both tools serve similar use cases in AI Agent Platforms. However, they also have distinct specializations: LobeChat extends into AI Chat Interfaces.
LobeChat provides self-hosting options for complete data control and customization, while AgentOS may be primarily cloud-based or require different deployment approaches.