# Agno vs CrewAI: 2026 Empirical Benchmark & Cost Shootout

> **Direct Answer (October 2026 Verdict)**: Agno (Phidata) wins on raw runtime performance with 3-microsecond agent instantiation, 7KB memory footprint (50x lighter), and 34.5% lower prompt token overhead across 42.7k+ GitHub stars (94.3), while CrewAI wins on rapid declarative YAML role/goal/backstory team prototyping and @persist Flows across 59.7k+ GitHub stars (93.2).

- **Category**: High-Speed Multi-Agent Runtime & Role Orchestration Shootout
- **Canonical URL**: https://exactbaseline.com/vs/agno-vs-crewai
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## Agno Key Advantages
- 42,765+ GitHub stars with 3us agent instantiation and 7KB memory footprint (50x lighter than CrewAI)
- 1.08x minimal prompt token overhead vs 1.65x in opinionated role-playing prompt wrappers
- Built-in Agent UI, multimodal tool routing, and native vector knowledge stores

## CrewAI Key Advantages
- 59,763+ GitHub stars with intuitive Role/Goal/Backstory abstractions that ship multi-agent crews in <30 LOC
- CrewAI Flows (@start, @listen, @router) combine deterministic event pipelines with autonomous agent teams
- Large pre-built CrewAI tool ecosystem for web scraping, RAG, and enterprise SaaS automation