> ## Documentation Index
> Fetch the complete documentation index at: https://docs.athina.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# How can I improve the performance / reliability of my evals?

LLM-graded Evals will never be perfect but here are some things you can do to improve their performance, and reduce flakiness.

**1. Use GPT-4** (especially if your eval task requires reasoning capabilities)

* `gpt-4` will perform *much* better than GPT 3.5 if your eval task is complex.
* For simple tasks, you can use `gpt-3.5-turbo` or sometimes an even cheaper model.

**2. Run the evals multiple times**

Running evals multiple times, and using a majority vote, or discarding inconsistent results will mitigate the flakiness.

**3. Provide custom examples**

Providing some custom few-shot examples suited to your use case are likely to improve the performance of your evals further.

**4. Set up [custom evals](/evals/custom-evals)**

Using a completely custom eval is likely the best way to tailor your eval to work perfectly for your use case.

**5. Contact Us**

Email us at [hello@athina.ai](mailto:hello@athina.ai) for help setting up a high-performing custom eval suite.