AI AGENT FRAMEWORKS
Head-to-Head Comparison

Dify vs CrewAI

Quick answer: CrewAI leads this head-to-head in 2026, scoring 89 on the Hyland Score against Dify's 85. It scores higher on the Hyland Score (89 vs 85). Choose Dify instead if your work fits the "No-Code Platform" category better.

Dify

LangGenius
85HYLAND SCORE

Visual, open-source LLM app builder.

Try Dify
HIGHER SCORE

CrewAI

CrewAI Inc
89HYLAND SCORE

Role-based multi-agent framework where agents have specific roles, goals, and backstories.

Try CrewAI

Spec-by-spec

SPEC
DIFY
CREWAI
Hyland Score
85
89
Category
No-Code Platform
Multi-Agent
Pricing
Freemium
Open Source
Open source
Yes
Yes
Self-hostable
Yes
Yes
Language
Python (backend), TS (UI)
Architecture
Visual workflows
License
Apache 2.0 (custom)
GitHub stars
~105K
24K
Languages
Python
Open source
Yes
Self-hostable
Yes
Free tier
Yes

Dify: strengths & weaknesses

  • Freemium pricing lowers the cost of getting started
  • Broader feature set out of the box
  • Lower Hyland Score (85 vs 89)

CrewAI: strengths & weaknesses

  • Higher Hyland Score (89 vs 85)
  • Open Source pricing lowers the cost of getting started
  • Narrower feature set than the alternative
The Verdict

Choose CrewAI for most teams

CrewAI comes out ahead because it scores higher on the Hyland Score (89 vs 85).

Choose Dify instead if your work fits the "No-Code Platform" category better.

Dify vs CrewAI: FAQ

Which is better, Dify or CrewAI?

Based on the Hyland Score, CrewAI leads with 89 vs 85, because it scores higher on the Hyland Score (89 vs 85). However, Choose Dify instead if your work fits the "No-Code Platform" category better.

Is Dify free to use?

Dify uses a Freemium pricing model. It is open source. It can be self-hosted.

Is CrewAI free to use?

CrewAI uses a Open Source pricing model. It is open source. It can be self-hosted.

Can I use Dify and CrewAI together?

Yes — many teams combine them. Dify strengths: visual, self-host, rag. CrewAI strengths: python, research, automation. Evaluate both against your actual workload before standardizing on one.

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