> 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/2.-get-started/first-evaluation.md).

# Your first evaluation

Run your first private evaluation in Stratix Premium — pick a model, pick a dataset, see scores in minutes.

A private evaluation runs a model against a dataset and scores the outputs. Here's the fastest way to do one.

## Prerequisites

* [ ] A Stratix Premium account ([sign up](/2.-get-started/sign-up.md))
* [ ] Either: a small dataset (CSV or JSONL with input → expected output columns), or willingness to use a starter dataset

## Steps

### 1. Open Evaluations

In the left rail, click **Evaluations**. Click **New evaluation**.

### 2. Pick a model

Search and select. The full public catalog is searchable, plus any BYOK custom models you've registered.

### 3. Pick a dataset

Two options:

* **Upload a dataset** — drag a CSV/JSONL onto the upload zone. Stratix infers the schema; you confirm input and expected-output columns.
* **Use a starter dataset** — pick a benchmark from the public catalog (e.g., MMLU subset).

### 4. Pick scoring

For your first eval, pick a code grader that fits your data:

* **Exact match** — outputs equal to expected
* **Semantic similarity** — fuzzy match using an embedding model
* **Regex match** — outputs match a pattern
* **JSON schema** — outputs validate against a schema

Skip judges for now — you'll build one later.

### 5. Preview cost

Stratix shows the worst-case ECU consumption before you run. Approve.

### 6. Run

Click **Run**. The evaluation queues; results stream in row-by-row.

### 7. Read the results

The results page shows:

* Overall score
* Per-row scores (input → output → score)
* Score distribution
* Latency and cost per row

## Verify

You should have a completed evaluation with a top-line score. Click any failing row to see the input, the model output, and the expected output side-by-side.

## What just happened

Stratix called the model on each input row, ran the scorer against each output, and aggregated the result. Every row is stored — you can re-open this evaluation later or compare it against a future run.

## What to try next

* **Run the same evaluation against a different model.** Stratix's compare-models view shows both runs side-by-side.
* **Iterate on the prompt.** If your dataset includes a prompt template column, change the template and rerun.
* **Add a judge.** See [First judge](/2.-get-started/first-judge.md) for subjective dimensions.

## Where to next

* [First judge](/2.-get-started/first-judge.md)
* [First trace](/2.-get-started/first-trace.md)
* [Tutorial: First evaluation in 10 minutes](/8.-evaluate-score-the-outputs/01-first-evaluation.md)
* [Stratix Premium — Evaluations](/8.-evaluate-score-the-outputs/evaluations.md)