Comparison

Patronus AI vs Ragas

On the evidence we track, Patronus AI leads this comparison with a composite score of 69/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.

Machine formatsJSONMarkdownGraphQLor send Accept: application/json
Patronus AI69
Ragas58
Score
Vioscale score
Patronus AI69 / 100low · 37%
Ragas58 / 100low · 27%
Pricing
Free tier
Patronus AI
Ragas
Model
Patronus AIfreemium
Price level
Patronus AImid
Ragasfree
Starting price
Patronus AI$25
Ragas
Transparent
Patronus AI
Ragas
Integrations
Count
Patronus AI5
Ragas3
Adoption
Dependent repos
Patronus AI
Ragas1
Github stars
Patronus AI
Ragas15,484
Release
Cadence days
Patronus AI
Ragas7
History
Patronus AI
License
Spdx
Patronus AI
Language
Primary
Patronus AI
RagasPython
Market
Availability

Capabilities

Feature-by-feature on the axes that matter for ai evals testing. “-” means undocumented, not absent.

Capabilities
Architecture model
Patronus AIManaged enterprise saas
RagasOpen source CLI
LLM as a judge prompt grading framework
Patronus AI
Ragas
Specialized rag metrics faithfulness context relevance
Patronus AI
Ragas-
Deterministic regex and json schema assertions
Patronus AI-
Ragas-
Synthetic test dataset generation from documents
Patronus AI-
Ragas
Ci cd github actions pipeline blocking gates
Patronus AI-
Ragas-
Red teaming and adversarial vulnerability scanning
Patronus AI
Ragas-
Multi model side by side ab regression testing
Patronus AI
Ragas-
Human in the loop hitl annotation UI
Patronus AI-
Ragas-
Dashboard analytics for metric drift over time
Patronus AI
Ragas-
SOC2 type ii
Patronus AI-
Ragas-
Mit or apache permissive oss license
Patronus AI
Ragas-
Pricing model
Patronus AIPer test execution cloud
RagasFree open source

What each one is

The product in its own terms, so the numbers below have context.

Patronus AI

Leader

A managed platform that evaluates language models and AI agents using specialized scoring models, provides adversarial test datasets, monitors performance in production, and enables side-by-side comparison and debugging of AI systems at scale.

Independently observed

Ragas

A Python-based framework that evaluates RAG applications through automatic metrics covering faithfulness, relevance, and recall. Includes tools to synthetically generate test datasets customized for specific use cases, enabling developers to assess LLM application performance at both component and end-to-end levels.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Patronus AI

Leader
from $25/moHybridFree tier

Free tiers available ($0/mo), paid plan from $25/mo, API pricing from $10/1k calls

  • DeveloperFree
    • $10 in free credits
    • Patronus Experiments (last 2 weeks)
    • Patronus Comparisons
    • Patronus Datasets
    • Optional Patronus API
  • IndividualFree
    • 20 pages
    • Customizable options
    • Secure data storage
    • Email support
  • Base$25/month for 600 pages
    • 600 pages
    • Page add-ons available
    • 24/7 customer support
    • Analytics and reporting
    • Account Management
  • EnterpriseContact sales
    • Unlimited pages and runs
    • On-premise or dedicated VPC deployment
    • Custom data retention
    • SSO
    • Premium Platform Features (Evaluation Runs, webhooks)
    • +3 more
as of verify ↗

Ragas

Open sourceFree tier
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
Patronus AI
Ragas
CLI
Patronus AI
Ragas
Deployment
Cloud / SaaS
Patronus AI
Ragas
Self-hosted
Patronus AI
Ragas
On-premise
Patronus AI
Ragas
Hybrid
Patronus AI
Ragas

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

Patronus AI

Leader
5 total
  • Smolagents
  • OpenAI Agents
  • Pydantic
  • CrewAI
  • Langchain
Independently observed

Ragas

3 total
  • LlamaIndex
  • LangSmith
  • OpenAI
Independently observed

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.