# Model Status

Model status can be cold and warm refer to how long it takes to launch a machine learning model to accept requests.

* **Cold Boot:** When a model hasn't been used in a while, it gets turned off to conserve resources. This is similar to completely turning off your computer. When you make a request to use the model again, it needs to be fully loaded and started up, which can take several minutes for large models. This is a cold boot.
* **Warm Boot:** If a model has been used recently, it stays loaded and ready to accept requests. This is similar to putting your computer in sleep mode. When you use a warm model, the response is much faster because the model is already up and running.

Here's why this happens:

* Segmind has a large library of models, and keeping them all running all the time would use a lot of resources.
* They only run the models that are actually being used.
* Cold boots happen more often for less frequently used models.

{% hint style="success" %}
Segmind only charges you for the time the model is actually processing your request, not the boot time. So, cold boots don't affect your costs.
{% endhint %}