Giskard vs HELM
A side-by-side comparison of two LLM Evaluation AI agents — to help you pick the right one.
Giskard
Giskard is an open-source library designed for testing and evaluating large language model (LLM) applications, with a focus on Retrieval-Augmented Generation (RAG) systems. It provides tools to assess model robustness, fairness, and performance, helping developers identify and mitigate issues in LLM outputs.
HELM
HELM (Holistic Evaluation of Language Models) is a comprehensive benchmarking framework designed to evaluate the performance of large language models (LLMs) across a wide range of tasks and scenarios. It provides standardized metrics and datasets to assess model capabilities, biases, and robustness, enabling systematic comparison of LLMs.
| Giskard | HELM | |
|---|---|---|
| Category | LLM Evaluation | LLM Evaluation |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Open Source |
Giskard: what it solves
It solves the challenge of systematically evaluating and improving the reliability and safety of LLM applications, particularly in complex workflows like RAG.
HELM: what it solves
It solves the lack of standardized, transparent, and holistic evaluation methods for comparing the performance and limitations of different language models.