LobeHub vs openmake_llm
AI agent workspaces compared
lobehub organizes agents, projects, and scheduled work in shared workspaces, while openmake_llm coordinates models, agents, and tools for multi-step workflows. lobehub emphasizes team collaboration and agent organization; openmake_llm emphasizes self-hosted model routing, persistent tasks, and controlled execution.
LobeHub: Organize AI Agents for 24/7 Operations
LobeHub is a TypeScript AI-agent workspace for hiring, scheduling, and getting reports from an AI team, so work can continue while you are away. Its full-stack app uses Next.js and a Vite SPA, with self-hosting options including Docker.
openmake_llm: Coordinate AI Models, Agents, and Tools
OpenMake is a self-hosted AI workspace that coordinates chat models, agents, and tools in one place. It suits people who want multi-step AI workflows with local or open-weight models, while keeping infrastructure and model choices under their control.
| LobeHub | openmake_llm | |
|---|---|---|
| Language | TypeScript | TypeScript |
| License | — | MIT |
| Stars | 83.3k | 43 |
| Forks | 16k | 7 |
| Last analyzed | Oct 20, 2026 | Oct 4, 2026 |
Key differences
- lobehub focuses on creating and coordinating agent teams around projects and shared context; openmake_llm routes work across models and capabilities such as planning, vision, and speech.
- lobehub offers scheduled agent runs and editable personal memory; openmake_llm describes persistent tasks with checkpoints, approvals, and parallel sub-agents.
- lobehub supports Docker or documented hosting platforms and requires configuring a model provider; openmake_llm is a self-hosted stack with supporting services such as PostgreSQL and Redis.
- lobehub reports 83k stars and 16k forks and is under active development; openmake_llm reports 43 stars and 7 forks, and identifies some capabilities as planned or opt-in.
- lobehub's repository metadata lists the license as NOASSERTION, while its README identifies a LobeHub Community License; openmake_llm lists MIT.
- Both projects use TypeScript, but lobehub centers on shared agent workflows, while openmake_llm is aimed at developers and teams managing infrastructure and model choices.
Choose LobeHub if you…
- want to organize agents, projects, and shared team work in one workspace.
- need scheduled agent runs and editable personal memory.
- prefer Docker or supported hosting options and can configure an AI model provider.
Choose openmake_llm if you…
- need to route work across local, open-weight, or hosted models assigned to different capabilities.
- want persistent multi-step agent tasks with checkpoints, approvals, or parallel sub-agents.
- can operate a self-hosted stack and want research reports or sandboxed agent execution.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.