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

# Pricing and Billing

Beam is serverless, which means your apps will scale-to-zero by default. Billing is based on the lifecycle of your containers. You are only charged when your containers are running.

## Price List

| Resource     | Price (Per Second)   | Price (Per Hour) |
| ------------ | -------------------- | ---------------- |
| CPU          | \$0.0000528 per core | \$0.190 per core |
| RAM          | \$0.0000056 per GB   | \$0.020 per GB   |
| RTX 4090 GPU | \$0.000192           | \$0.69           |
| A10G GPU     | \$0.000292           | \$1.05           |
| H100 GPU     | \$0.000972           | \$3.50           |
| File Storage | Included             | Included         |

## What am I charged for?

You are charged whenever a container is running. This includes:

* Running any code you've defined in an [`on_start`](/v2/endpoint/loaders) function
* Running your application code
* Any [`keep_warm_seconds`](/v2/endpoint/keep-warm) you've set

## What am I *not* charged for?

* Waiting for a machine to start
* Pulling your container image

## Default Container Spin-down Times

After handling a request, Beam keeps containers running ("warm") for a certain amount of time in order to quickly handle future requests. By default, these are the container "keep warm" times for each deployment type:

| Deployment Type         | Container Keep Warm Duration |
| ----------------------- | ---------------------------- |
| Endpoints/ASGI/Realtime | 180s                         |
| Task Queues             | 10s                          |
| Pods                    | 600s                         |

## Real-World Example

You've deployed a REST API. You've added two Python Packages in your `Image()`, which are loaded when your app first starts.

You've also added a `keep_warm_seconds=300`, which will keep the container alive for 300 seconds (5 minutes) after each request.

```python app.py theme={null}
from beam import endpoint


# This runs once when the container first starts
def load_models():
    return {}

@endpoint(keep_warm_seconds=300, on_start=load_models)
def predict():
    return {}
```

Let's pretend you deploy this and call the API. Suppose it takes:

* 1s to boot your application and run your `on_start` function.
* 100ms to run your task.
* 300s to keep the container alive, based on the `keep_warm_seconds` argument.

You would be billed for a total of 301.1 seconds.