Agno vs CrewAI: Agent Frameworks Comparison
Compare Agno and CrewAI side by side. Both are tools in the Agent Frameworks category.
Updated April 29, 2026
The short answer
Choose Agno if production-first design with stateless scaling and AgentOS runtime.
Choose CrewAI if 5.7x faster to deploy than competitors for structured business tasks.
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Quick Comparison
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Free open-source | Open Source |
| Best For | Python teams building production AI agents that want first-class deployment, observability, and multi-agent support | Developers who want to build multi-agent systems where specialized agents collaborate |
| Website | agno.com | crewai.com |
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Pros & Cons: Agno vs CrewAI
- +Production-first design with stateless scaling and AgentOS runtime
- +39K+ GitHub stars and 424 active contributors
- +100+ pre-built tools including MCP support
- +Control plane UI is rare in OSS agent frameworks
- +Memory in your DB — no vendor lock-in
- −Newer than LangChain ecosystem — fewer third-party integrations
- −Python-only — no JS/TS SDK
- −Smaller community than LangChain at production scale
- −Less battle-tested at Fortune 500 scale than LangGraph
- +5.7x faster to deploy than competitors for structured business tasks
- +Excellent role-based abstraction for multi-agent collaboration
- +Strong documentation and ease of use with 4.7 rating
- +Free open-source option for self-hosted deployments
- −Prohibitively expensive—USD 99/month to USD 120,000/year pricing gaps
- −Excessively robust for simple tasks requiring lighter alternatives
- −Code-heavy Python framework lacks visual workflow overview
- −Limited control flow for complex conditional branching needs
Pricing: Agno vs CrewAI
- · Full Python SDK + AgentOS runtime
- · Control plane UI included
- · 100+ tool integrations + MCP
- · Apache 2.0 license
- · Self-hosted
- · Full framework access
- · Community support
- · Unlimited agents
- · Fixed execution quota
- · Hosted infrastructure
- · Email support
- · LLM costs separate
- · Custom execution limits
- · Dedicated support
- · SLA guarantees
- · Advanced features
What people are saying
Curated quotes from Hacker News, Reddit, Product Hunt, and review blogs. Dates shown so you can judge whether early criticism still applies.
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“Agno has emerged as one of the fastest-growing AI agent frameworks in 2026 — 39,100+ stars and a 424-contributor community.”
— DecisionCrafters review, DecisionCrafters · Apr 2026 - +
“Purpose-built for production with stateless scaling, session management, and enterprise features — closer to a 'framework + runtime + control plane' than just an SDK.”
— WorkOS engineering blog, WorkOS Blog · Mar 2026 - +
“Memory is stored in your database — you own the data, not the vendor. That alone made it the right call for our compliance posture.”
— Production team review, DecisionCrafters · Mar 2026 - ·
“Smaller community than LangChain at production scale — but the documentation gap is closing fast.”
— Framework comparison, AI Agents Directory · Mar 2026
When to Choose Agno vs CrewAI
- Production multi-agent systems with stateless scaling
- Customer-facing AI assistants with session management
- Internal-tool agents with monitoring dashboards
- Multi-agent team workflows
- Automated research and content pipelines
- Business process automation with AI teams
How to Choose a Agent Frameworks Tool
Key criteria to evaluate when comparing Agent Frameworks solutions:
About Agno
Agno (formerly Phidata) is an open-source Python framework for building production-grade AI agents and multi-agent systems. With 39,100+ GitHub stars and an active 424-contributor community, it's emerged as one of the fastest-growing agent frameworks in 2026.
Agno provides three integrated layers: a Python SDK for building individual agents and multi-agent teams, a stateless FastAPI runtime called AgentOS for production deployment, and a control plane UI for monitoring, session management, and team operations. It supports 23+ LLM providers (OpenAI, Anthropic Claude, Google Gemini, and more) and ships 100+ pre-built tool integrations including web search, data analysis, file operations, and Model Context Protocol (MCP) servers.
Memory and knowledge systems are first-class: user memories, session memories, and RAG knowledge bases are stored in your database — you own the data, not Agno. Recent v2.5.13 (March 2026) added ReliabilityEval for agent evaluation, enhanced AgentOS APIs for session management, and Slack interface improvements. Agno is positioned as the production-first alternative to LangChain/LangGraph for Python teams.
About CrewAI
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.
What is Agent Frameworks?
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworkstools →Frequently Asked Questions
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