# Evaluate & Test

- [Overview](https://docs.fiddler.ai/evaluate-and-test/overview.md): Hands-on quick start guides for evaluating LLM applications, testing with custom LLM-as-a-Judge metrics, and comparing model outputs using Fiddler Experiments.
- [Evaluator Rules](https://docs.fiddler.ai/evaluate-and-test/evaluator-rules.md): Configure automated evaluations for your GenAI application spans using Evaluator Rules. Learn to map evaluators to span data, define application rules, and manage backfill configuration.
- [Evals SDK Quick Start](https://docs.fiddler.ai/evaluate-and-test/evals-sdk-quick-start.md): Learn how to evaluate Large Language Model (LLM) applications, RAG systems, and AI agents using the Fiddler Evals SDK with built-in and custom evaluators.
- [Prompt Specs Quick Start](https://docs.fiddler.ai/evaluate-and-test/prompt-specs-quick-start.md): Get started with Fiddler's LLM-as-a-Judge evaluation using Prompt Specs in minutes. Learn to create custom evaluations, test them, and deploy to production monitoring.
- [Compare LLM Outputs](https://docs.fiddler.ai/evaluate-and-test/llm-evaluation-example.md): Learn how to systematically compare outputs from different LLM models (GPT-3.5, Claude, etc.) using Fiddler's pre-production evaluation environment to make data-driven model selection decisions.
- [Multimodal Evaluators](https://docs.fiddler.ai/evaluate-and-test/multimodal-evaluators.md): Evaluate GenAI outputs involving images and documents using vision-capable models. Monitor document processing pipelines for extraction accuracy and summarization faithfulness.


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