Jury
Evaluate NLP model outputs with automated text-to-text metrics.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Jury?
Jury is an easy-to-use tool for evaluating Natural Language Generation (NLG) models, providing various automated text-to-text metrics to assess the quality of generated texts. It simplifies the process of measuring and comparing NLG model performance.
Key differentiator
“Jury stands out as an open-source, Python-based tool specifically tailored for evaluating NLG models using automated text-to-text metrics, offering easy integration and community-driven support.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Documentation and examples focus on English, with no clear support for other languages
Evaluation of NLG models on large text corpora can lead to significant slowdowns or memory errors
Fit analysis
Who is it for?
✓ Best for
Research teams needing a comprehensive set of evaluation metrics for NLG models
Developers integrating automated text-to-text metrics into their NLP pipelines
Data scientists who require easy integration and community support
✕ Not a fit for
Projects requiring real-time performance evaluation (Jury is designed for batch processing)
Teams looking for a cloud-based service with managed backend operations
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with Jury
Step-by-step setup guide with code examples and common gotchas.