Lagent vs OpenHuman
Side-by-side comparison of two AI agent tools
Short answer
- OpenHuman is growing faster: +3,180 GitHub stars in the last 30 days vs +7 for Lagent.
- Pick Lagent for: a lightweight framework for building LLM-based agents. Pick OpenHuman for: openHuman is the fastest, cheapest, most efficient open-source agent harness.
From GitHub data refreshed daily.
Lagentopen-source
A lightweight framework for building LLM-based agents
O
OpenHumanopen-source
OpenHuman is the fastest, cheapest, most efficient open-source agent harness. Written in Rust
Metrics
| Lagent | OpenHuman | |
|---|---|---|
| Stars | 2.3k | 40.4k |
| Star velocity /mo | 7.301587301587301 | 3.2k |
| Commits (90d) | 0 | 22.6k |
| Releases (6m) | 1 | 10 |
| Overall score | 0.2559589056610766 | 0.9408550749378012 |
Pros
- +PyTorch-inspired design makes agent workflows intuitive for ML practitioners familiar with neural network concepts
- +Built-in memory management automatically handles message storage and state persistence across agent interactions
- +Lightweight architecture with clean abstractions that simplify multi-agent system development and reduce boilerplate code
Cons
- -Limited to source installation only, which may complicate deployment in production environments
- -Documentation appears minimal based on available information, potentially creating barriers for new users
Use Cases
- •Building conversational AI systems that require multiple specialized agents working together on complex tasks
- •Research prototyping for multi-agent reinforcement learning and collaborative AI experiments
- •Creating intelligent automation workflows where different LLM agents handle specific aspects of a larger process
FAQ
- Which is more popular, Lagent or OpenHuman?
- OpenHuman has more GitHub stars (40,447 vs 2,280).
- Which is more actively developed, Lagent or OpenHuman?
- OpenHuman had more commits in the last 90 days (22,600 vs 0).
- Should I use Lagent or OpenHuman?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.