Which is more popular, AIOS or LangChain?

LangChain has more GitHub stars (147,399 vs 6,442).

Which is more actively developed, AIOS or LangChain?

LangChain had more commits in the last 90 days (542 vs 19).

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

LangChain is growing faster: +23,097 GitHub stars in the last 30 days vs +165 for AIOS.
Pick AIOS for: aIOS: AI Agent Operating System. Pick LangChain for: the agent engineering platform.

From GitHub data refreshed daily.

AIOS: AI Agent Operating System

LangChainopen-source

The agent engineering platform

+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

+Extensive ecosystem with seamless integration between LangGraph, LangSmith, and hundreds of third-party components
+Future-proof architecture that adapts to evolving LLM technologies without requiring application rewrites
+Strong community support with 131k+ GitHub stars and comprehensive documentation for both Python and JavaScript

-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

-Significant learning curve due to the framework's extensive feature set and multiple abstraction layers
-Potential over-engineering for simple use cases that might be better served by direct API calls
-Heavy dependency on the LangChain ecosystem which can create vendor lock-in concerns

•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 complex multi-agent systems that require planning, tool use, and coordination between different AI components
•Creating production LLM applications with observability, debugging, and deployment infrastructure via LangSmith
•Developing chatbots and conversational AI with memory, context management, and integration with external data sources

Which is more popular, AIOS or LangChain?: LangChain has more GitHub stars (147,399 vs 6,442).
Which is more actively developed, AIOS or LangChain?: LangChain had more commits in the last 90 days (542 vs 19).
Should I use AIOS or LangChain?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.