LangGraph vs Strands: Agent Frameworks Comparison

LangGraph is LangChain's graph-based orchestration framework for building stateful, multi-step AI agents. Unlike linear chains, LangGraph models agent workflows as directed graphs with nodes (functions or LLM calls) and edges (conditional routing), enabling cycles, branching, parallel execution, and durable state across long-running interactions.

Together, LangChain and LangGraph have 90M monthly downloads and power production applications at Uber, JPMorgan, BlackRock, and Cisco. LangGraph 1.0 (released 2026) added enterprise certifications, durable execution with checkpointing, time-travel debugging, and human-in-the-loop interrupts. LangChain 1.0 now uses LangGraph under the hood — start with the simple LangChain API and drop down to LangGraph for advanced control when needed.

LangGraph is fully MIT-licensed open-source and free. LangSmith (the observability and eval companion) and LangGraph Platform (managed deployment) are paid SaaS offerings on top. Positioned as the production-control framework for teams that need reliability, observability, and durability — the most enterprise-ready open-source agent framework in 2026.

Strands Agents is an open-source AI agent SDK developed by AWS that takes a model-driven approach to building and running AI agents in just a few lines of code. Launched as a preview in May 2025, Strands reached version 1.0 in July 2025, bringing production-ready multi-agent orchestration capabilities. The framework uses the reasoning abilities of modern LLMs to handle planning and tool usage autonomously, eliminating the need for hardcoding complex task flows.

Strands is actively used in production by multiple AWS teams, including Kiro, Amazon Q Developer, and AWS Glue. The SDK supports multiple AI providers including Amazon Bedrock, Anthropic, Gemini, LiteLLM, Llama, Ollama, OpenAI, and Writer, making it truly provider-agnostic. Strands 1.0 introduced new primitives for multi-agent architectures, support for the Agent-to-Agent (A2A) protocol, a session manager for retrieving agent state from remote datastores, and improved async support throughout the SDK.

The framework offers comprehensive features including multi-modal support (text, speech, and image processing), rich AWS service integrations, extensibility for custom tools, and robust observability capabilities. With natural language workflow definitions through Agent SOPs and integration with Model Context Protocol (MCP), Strands provides a modern, scalable approach to building production-grade AI agents.