HELM vs LangSmith
A side-by-side comparison of two LLM Evaluation AI agents — to help you pick the right one.
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.
LangSmith
LangSmith is a platform integrated with the LangChain framework, designed for evaluating, monitoring, and collaborating on LLM applications. It supports human-in-the-loop workflows, logging, and performance tracking for LLM-based systems.
| HELM | LangSmith | |
|---|---|---|
| Category | LLM Evaluation | LLM Evaluation |
| Open source | Yes | Not publicly specified |
| Self-hostable | Yes | Not publicly specified |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Paid |
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.
LangSmith: what it solves
It streamlines the evaluation and iterative improvement of LLM applications by providing tools for logging, monitoring, and human feedback integration.