> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/5.-select-pick-the-model/public-evaluation-spaces.md).

# Public evaluation spaces

An **evaluation space** is a workspace bundling a model selection, a dataset/benchmark selection, and a scoring config. Public spaces are curated by LayerLens and partners — browse them to see how seasoned teams structure evaluations.

URL: [`stratix.layerlens.ai/spaces`](https://stratix.layerlens.ai/spaces)

## What's in a space

* **Model selection** — one or more models being evaluated
* **Dataset / benchmark selection** — what's being evaluated against
* **Scoring config** — which scorers and judges
* **Latest run results** — top-line scores and detail
* **Description and methodology notes** — context for why this space exists

## How to use public spaces

* **Read for inspiration.** A well-structured space is a recipe for "how to evaluate X."
* **Replicate.** Use the same models, the same benchmarks, the same scoring on your own dataset. Premium evaluations let you instantiate a similar configuration.
* **Compare.** Run the same evaluation against your data and see how your results compare to the public space.

## Browse and filter

* Search by name or description
* Filter by capability — code, reasoning, multilingual, etc.
* Filter by industry tag
* Sort by recency or by activity

## Premium evaluation spaces

Premium adds **private spaces** that are scoped to your org. The shape is identical — model + dataset + scoring + results — but visibility is private.

## Where to next

* [Premium — Spaces](/8.-evaluate-score-the-outputs/spaces.md)
* [Concept: Evaluation spaces](/8.-evaluate-score-the-outputs/evaluation-spaces.md)
* [Models catalog](/5.-select-pick-the-model/models-catalog.md)
* [Public evaluations](/5.-select-pick-the-model/public-evaluations.md)


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