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OpenAI Evals
OpenAI's open-source framework for building and running custom LLM evaluations.
VS
At a Glance
| Attribute | OpenAI Evals | HELM |
|---|---|---|
| License / Pricing | Open Source | Free |
| Type | ai | ai |
| GitHub Stars | — | — |
| Rating | 4.2/5 | 4.3/5 |
| Key Features | 6 listed | 6 listed |
| Integrations | 4 listed | 4 listed |
| Categories | LLM Evaluation | LLM Evaluation |
Key Features
OpenAI Evals
- Built-in eval types: match, includes, fuzzy match, model-graded
- Model-graded evals for open-ended responses
- Custom eval definition via YAML
- Eval registry with hundreds of community-contributed benchmarks
- Compare performance across model versions
- Integration with OpenAI API for automated scoring
HELM
- Holistic metrics: accuracy, calibration, robustness, fairness, bias, efficiency
- 42 scenarios covering NLP, coding, reasoning, and knowledge tasks
- Standardized prompting methodology for fair model comparison
- Public leaderboard comparing GPT-4, Claude, Llama, Gemini, and more
- Modular scenario and metric system for custom evaluations
- Supports local models via HuggingFace and API models
Real-World Use Cases
OpenAI Evals
Measure quality before upgrading model versions
Define eval tasks from your real production use cases
Build a domain-specific benchmark
Collect 50–100 representative queries from your application logs
HELM
Compare models for a regulated industry use case
Select HELM scenarios relevant to your domain (e.g. medical QA, legal reasoning)
Integrations
OpenAI Evals
openailangsmithwandbdeepeval
HELM
huggingfaceopenaianthropicwandb
🏆 Which should you choose?
Choose OpenAI Evals if…
- → you need a fully open-source, self-hosted solution with no vendor lock-in
Choose HELM if…
- → you want a managed or commercial offering with enterprise support and SLAs