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

# Model Confidence Metrics

> Understand your AI's certainty in its responses with Galileo's model confidence metrics

Model confidence metrics help you gauge how certain your AI is about its answers. These metrics are useful for flagging uncertain responses, improving reliability, and knowing when to involve a human in the loop.

Use these metrics when you want to:

* Identify responses where the model is unsure or likely to make mistakes.
* Improve user trust by surfacing confidence scores or warnings.
* Analyze which prompts or situations are most challenging for your AI.

Below is a quick reference table of all model confidence metrics:

| Name                                                                      | Description                                                                | Supported Nodes | When to Use                                                                                      | Example Use Case                                                                                   |
| :------------------------------------------------------------------------ | :------------------------------------------------------------------------- | :-------------- | :----------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------- |
| [Prompt Perplexity](/concepts/metrics/model-confidence/prompt-perplexity) | Evaluates how difficult or unusual the prompt is for the model to process. | LLM span        | When you want to identify prompts that may confuse the model or lead to lower-quality responses. | Detecting outlier prompts in a customer support chatbot to improve prompt engineering.             |
| [Uncertainty](/concepts/metrics/model-confidence/uncertainty)             | Measures the model's confidence in its generated response.                 | LLM span        | When you want to understand how certain the model is about its answers.                          | Flagging responses where the model is unsure, so a human can review them before sending to a user. |

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## Next steps

* [Back to Metrics Overview](/concepts/metrics/overview)
* [Compare all metrics](/concepts/metrics/metric-comparison)