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CrewAI vs DSPy

Side-by-side comparison with live GitHub signals. Last updated May 16, 2026.

C

CrewAI

Multi-agent orchestration framework for collaborative AI workflows

OSSFree
51.5Ktoday296
D

DSPy

Framework for programming — not prompting — LLMs — 33K+ stars

OSSFree
34.5Ktoday393
MetricCrewAIDSPy
GitHub Stars51.5K34.5K
Contributors296393
Last CommitMay 15, 2026May 15, 2026
Open Issues316474
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Shared Tags

python

Only in CrewAI

multi-agentorchestrationrolestaskscollaboration

Only in DSPy

prompt-optimizationprogrammingresearchragstanfordopen-source

About CrewAI

CrewAI is a lean, fast multi-agent orchestration framework that lets you define autonomous AI agents with distinct roles, goals, and backstories, then assign them tasks within a structured crew. Agents collaborate, delegate, and pass context to each other using a role-playing paradigm that maps naturally to real team workflows. CrewAI supports sequential and hierarchical process flows, integrates with LangChain tools, and ships with a CLI for scaffolding new projects. It is the go-to framework for task-driven multi-agent systems without heavy infrastructure overhead.

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About DSPy

DSPy replaces prompt engineering with programming. Instead of writing prompts, you define modules with input/output signatures and DSPy automatically optimizes the prompts and weights for your pipeline. Supports chain-of-thought, retrieval-augmented generation, and multi-hop reasoning patterns. From Stanford NLP.

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