Which is more popular, AIOS or Lagent?

AIOS has more GitHub stars (6,442 vs 2,281).

Which is more actively developed, AIOS or Lagent?

AIOS had more commits in the last 90 days (19 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

AIOS is growing faster: +165 GitHub stars in the last 30 days vs +7 for Lagent.
Pick AIOS for: aIOS: AI Agent Operating System. Pick Lagent for: a lightweight framework for building LLM-based agents.

From GitHub data refreshed daily.

AIOS: AI Agent Operating System

Lagentopen-source

A lightweight framework for building LLM-based agents

+Comprehensive resource management with dedicated modules for LLM, memory, storage, and tool management
+Dual interface support with both Web UI and Terminal UI for flexible development workflows
+Modular architecture separating kernel and SDK concerns, allowing focused development on either system-level or application-level features

+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

-High complexity as an operating system-level solution may present steep learning curve for developers
-Requires understanding of both kernel and SDK components for full utilization
-Appears to be primarily research-focused, potentially limiting production readiness

-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

•Development and deployment of complex LLM-based AI agents requiring comprehensive resource management
•Building computer-use agents that need VM control and computer contextualization capabilities
•Research projects exploring AI agent operating system architectures and agent ecosystem development

•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

Which is more popular, AIOS or Lagent?: AIOS has more GitHub stars (6,442 vs 2,281).
Which is more actively developed, AIOS or Lagent?: AIOS had more commits in the last 90 days (19 vs 0).
Should I use AIOS or Lagent?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.