CrewAI vs Strands: Agent Frameworks Comparison

CrewAI is a multi-agent orchestration platform that enables developers to build autonomous AI agent teams with role-based collaboration. Founded as an open-source framework, CrewAI allows developers to define agents with specific roles, goals, and tools that execute tasks in parallel with clear delegation. The platform has strong ratings (4.7 from 238 reviews) and is praised for ease of use, high-quality documentation, and being 5.7x faster to deploy than competitors for structured business tasks. CrewAI offers three tiers: a free open-source version, cloud plans starting at USD 99/month, and enterprise pricing up to USD 120,000/year. Each plan includes fixed monthly execution quotas limiting how many tasks agents can run before requiring an upgrade, with LLM and third-party tool costs billed separately by providers. While CrewAI excels at role-based multi-agent systems for business workflows like content marketing and lead scoring, users find it excessively robust for simple tasks, code-heavy requiring Python expertise, and limited in control flow for complex conditional branching. The platform has a smaller ecosystem compared to alternatives like LangGraph.

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.