Our verdict
We have not reviewed OLMO-eval yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About OLMO-eval
OLMO-eval is a Python-based evaluation suite for large language models (LLMs). It provides standardized benchmarks and metrics to assess model performance across multiple tasks.
Best for
Researchers and developers evaluating OLMo or compatible LLMs with reproducible benchmarks
Use cases
- Running reproducible evaluations on LLMs using established benchmarks
- Comparing performance of different model versions or configurations
- Integrating evaluation pipelines into model training workflows
Notes
379 stars on GitHub. Last updated 2025-07-11. Licensed Apache-2.0.
Pros
- Open-source and community-maintained under the Allen AI umbrella
- Simplifies running standard LLM evaluations with a single Python framework
Cons
- Small star count (379) indicates limited community adoption and support
- Primarily designed for OLMo models, may require adaptation for other architectures
Key facts
What we have checked
- GitHub stars
- 72
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How OLMO-eval is growing
379 to 72
Alternatives
Alternatives to OLMO-eval
| Record | Type | How we know | Checked |
|---|---|---|---|
| lm-evaluation-harnessThis is an alternative to it | Open source | Named in the listing | Not dated |
| OpenAI EvalsThis is an alternative to it | Open source | Named in the listing | Not dated |
Compare
Compare OLMO-eval side by side
Sources
Where this comes from
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
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