HELM

Stanford CRFM's open-source Python...

4.0| Editor Rating

China

Editor Review

HELM's holistic evaluation and Stanford CRFM make it widely cited. Multiple leaderboards (capability, safety, VHELM, domain). Multilingual. pip install crfm-helm. Best for LLM researchers, transparent evaluation.

AI Tools Navigator Editorial TeamUpdated: 2026-02-11

What is HELM

HELM is Stanford CRFM's open-source Python framework for holistic, reproducible, transparent LLM evaluation. Standardized datasets (MMLU-Pro, GPQA, IFEval, WildBench), unified model access, metrics beyond accuracy (efficiency, bias, toxicity), Web UI and leaderboards.

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Basic Info

Category:

Country:China

Best For

Researchers

Difficulty: Intermediate

HELM Key Features

Holistic Framework
Beyond accuracy: efficiency, bias, toxicity metrics
Multi-domain Leaderboards
Capability, safety, VHELM, medical, finance leaderboards
Standardized Reproducible
Unified datasets and model access, CLI and Web UI

HELM Key Advantages

Stanford CRFM背书
Multi-dimensional metrics
pip install, multi-domain leaderboards

HELM Use Cases

Academic Research
Researchers use HELM for reproducible, transparent evaluation
Multi-dimensional Analysis
Analyze model characteristics via efficiency, bias, etc.