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Ragas vs Dify

RagasDify

Bottom line: Ragas for teams evaluating RAG pipelines; Dify for teams building LLM apps and agents quickly.

RagasRagas

Open-source evaluation toolkit for RAG and LLM applications.

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DifyDify

Open-source platform for building production-ready LLM apps and agents.

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Votes00
PricingFreeFreemium
CategoryCodingCoding
Tags
ragllm-evaluationopen-sourcetestingmetrics
llmopsopen-sourceai-agentsragworkflow
Best for
  • Teams evaluating RAG pipelines
  • Developers adding eval to CI/CD
  • RAG researchers and practitioners
  • Teams building LLM apps and agents quickly
  • Organizations with data-residency needs
  • Developers who want an open-source, self-hostable stack
Pros
  • Focused, research-backed RAG metrics
  • Free and open source
  • Reduces need for manual labeling via LLM scoring
  • Synthetic test-set generation
  • Broadened to LLM and agent evaluation
  • Genuinely open-source and self-hostable for strong data control
  • All-in-one: workflow, RAG, agents, and prompt IDE in one workspace
  • Low-code visual canvas lowers the barrier to building
  • Broad model and provider support, including self-hosted models
  • Large, active community and a marketplace ecosystem
Cons
  • LLM-as-a-judge scores need validation
  • Mainly a library; you build dashboards/infra
  • Judge model choice affects reliability and cost
  • Python-only
  • Less turnkey than managed eval platforms
  • License is not fully permissive; multi-tenant resale and branding removal are prohibited
  • Real cost is dominated by separate LLM token spend, not the platform fee
  • Message-credit model on paid tiers can feel limiting at scale
  • Self-hosting adds ops and maintenance burden
  • Free tier's one-time credits are essentially a demo allowance

Comparison generated from each tool's listing. Add or remove tools above to change it.