LLM Comparator
LLM Comparator is an interactive data visualization tool for evaluating and analyzing LLM responses side-by-side, developed by the PAIR team.
No commits in 23 months — may not be actively maintained. See maintained alternatives →
open-sourceobservability-evaluation
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Deep Analysis
Key Differentiator
vs generic eval dashboards: combines visual analytics with rationale clustering and custom field analysis to identify specific behavioral differences between models — from Google PAIR team
⚡ Capabilities
- • Interactive visualization for side-by-side LLM evaluation results
- • Qualitative difference discovery at example and slice levels
- • Rationale clustering to identify behavioral patterns between models
- • Custom field analysis for prompt category breakdowns
- • Python library for generating analysis JSON from evaluation data
- • Support for LLM-as-a-judge evaluation methods
🔗 Integrations
Google Vertex AI AutoSxSChatbot ArenaJupyter notebooks
✓ Best For
- ✓ Comparing two LLM outputs with numerical evaluation scores
- ✓ Discovering when and why one model outperforms another
- ✓ Analyzing response patterns across prompt categories
✗ Not Ideal For
- ✗ Comparing more than two models simultaneously
- ✗ Unstructured qualitative feedback without scoring
- ✗ Real-time model monitoring in production
Languages
TypeScriptJavaScriptPython
Deployment
Hosted web app (GitHub Pages)local npm buildPython PyPI package for data generation
⚠ Known Limitations
- ⚠ Research project in active development with expected bugs
- ⚠ Compares only two models simultaneously
- ⚠ Requires properly formatted JSON input following specific schema
- ⚠ Small development team with limited support
Alternatives
C
ChainForge
An open-source visual programming environment for battle-testing prompts to LLMs.
P
Promptfoo
Open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps
D
DeepEval
The LLM Evaluation Framework
U
UpTrain
Open-source platform to evaluate and improve generative AI applications with 20+ preconfigured evaluations
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