HELM vs TruLens
HELM
crfm.stanford.eduTruLens
trulens.orgSide by side
| Figure | HELM | TruLens |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · LLM Evaluation Tools | 8.3 (#7) | 7.9 (#9) |
| Spec score · AI LLM Evaluation Tools | 8.4 (#12) | 8.0 (#16) |
| Installation | The project instructs users to install HELM from PyPI with `pip install crfm-helm`. | The documented installation uses Conda with Python 3, followed by pip install trulens; source development uses the GitHub repository and editable installation. |
| Purpose | HELM is an open-source Python framework for holistic, reproducible, and transparent evaluation of foundation models, including language and multimodal models. | TruLens evaluates and traces AI agents to help find failures and reduce costs while maintaining quality. |
| Support | Users are directed to open GitHub issues for questions, which maintainers address when bandwidth is available. | The getting-started documentation points users to a community Slack. |
Plans
In their own words
HELM
HELM is an open-source Python framework for evaluating foundation models, including large language and multimodal systems. It supplies standardized datasets and benchmarks such as MMLU-Pro, GPQA, IFEval, and WildBench, with a unified interface for models from providers including OpenAI, Anthropic, and Google. Evaluations can examine accuracy, efficiency, bias, and toxicity, and can include custom metrics, LLM-as-a-judge checks, safety evaluations, and human review workflows. Users can configure private checkpoints or model servers, run inference locally, or send requests to an API. A web interface displays individual prompts and responses, while leaderboards compare models and benchmarks across areas such as medicine, finance, multilinguality, and world knowledge. HELM can reproduce published evaluation results and documents commands for running benchmarks, summarizing results, and starting a local server. It is free, Apache-2.0 licensed, and entered maintenance mode on June 1, 2026.