> 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/benchmarks-catalog.md).

# Benchmarks catalog

The Stratix Public Benchmarks catalog is the broadest open-browsable collection of LLM benchmarks. 52+ benchmarks, each with documented methodology, sample tasks, and per-model scores.

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

## What you can see for each benchmark

* **Description** — what the benchmark measures
* **Methodology** — how scoring works, sample size, harness notes
* **Sample tasks** — representative inputs from the benchmark
* **Per-model scores** — every model evaluated against this benchmark
* **Top performers** — leaderboard for this specific benchmark
* **Score-history-over-time** — how the frontier moved on this benchmark

## Filtering

* Capability — reasoning, code, math, multilingual, vision, multi-turn
* Difficulty — easy / medium / hard
* Sample size — small / medium / large
* License — open / restricted

## Sorting

* Alphabetical
* By difficulty
* By number of models evaluated
* By recency

## Per-benchmark page

Each benchmark has a dedicated page with:

* Hero card (name, capability, sample size)
* Full methodology notes
* Sample tasks (a representative subset)
* Score table with every model's result
* Top-N leaderboard
* Score-history chart
* Linked public evaluations

## Picking a benchmark

The hardest part of using benchmarks is picking the right ones. Some heuristics:

* **Don't pick more than 3-5.** More benchmarks doesn't mean more signal.
* **Match capability to task.** Code task → HumanEval/MBPP. Math task → MATH/GSM8K. General reasoning → MMLU/ARC.
* **Validate that the benchmark's distribution matches yours.** A model that scores high on a benchmark drawn from a totally different domain doesn't help you.

## Quarterly methodology updates

Each quarterly research report documents methodology changes for the quarter — new benchmarks added, scoring changes, harness updates. This is the most rigorous public discussion of benchmark methodology you'll find.

## Want to run your own benchmarks?

The Public catalog scores models against an open library of benchmarks. If your task is domain-specific — pricing in your tariff, citing your jurisdiction, answering against your documents — public benchmarks narrow the field but won't decide.

[**Stratix Premium**](/5.-select-pick-the-model/benchmarks.md) lets you author **custom benchmarks** from your own data and run the same candidate models against them. Custom benchmarks live in your workspace, are versioned, and rerun on demand whenever a new model lands in the catalog. See [Stratix Premium → Benchmarks](/5.-select-pick-the-model/benchmarks.md) for the custom-benchmark workflow.

## Where to next

* [Models catalog](/5.-select-pick-the-model/models-catalog.md)
* [Public evaluations](/5.-select-pick-the-model/public-evaluations.md)
* [Quarterly reports](/5.-select-pick-the-model/quarterly-reports.md)
* [Concept: Models and benchmarks](/5.-select-pick-the-model/models-and-benchmarks.md)


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