HELM
Definition
HELM is a framework and evaluation approach for standardized, multidimensional assessment of language and foundation models.
HELM systematically organizes scenarios and metrics and measures, besides accuracy, aspects such as robustness, fairness, bias, toxicity, and efficiency, as available for each scenario.
Simply explained
Like a test bench that does not assign just a single grade but tests a model from multiple perspectives.
Why it matters in practice
Relevant for robust model selection because a single benchmark rarely covers all business-critical criteria.
Example from business
A company uses a HELM-like evaluation matrix of quality, cost, latency, robustness, and own tasks.
Limits and pitfalls
- Misunderstanding HELM as complete coverage of all risks; using public benchmarks without own test cases; mixing various metrics into an unclear overall score.
Origin & history
Liang et al. introduced HELM in 2022 to make language models more transparent and standardized across many scenarios and metrics.
Use in mid-sized companies
- Possible application: structured evaluation framework for multiple model candidates and own use cases.
Frequently asked questions
Is HELM a single benchmark?
It is an evaluation framework with many scenarios and metrics. Does it replace company evaluations? No.
Sources
- Holistic Evaluation of Language Models · Liang et al. (2022), Holistic Evaluation of Language Models
- HELM Repository · HELM Repository
Sources checked on 10.10.2026.
Editorially reviewed on: