Pricing and Billing

Inference Providers is a production-ready service involving external partners and is therefore a paid product. However, as a Hugging Face user, you get monthly credits to run experiments. The amount of credits you get depends on your type of account:

To benefit from Enterprise Hub included credits, you need to explicitly specify the organization to be billed when performing the inference requests. See the Organization Billing section below for more details.

Pay-as-you-Go

PRO users and Enterprise Hub organizations can continue using the API once their monthly included credits are exhausted. This billing model, known as “Pay-as-you-Go” (PAYG), is charged on top of the monthly subscription. PAYG is only available for providers that are integrated with our billing system. We’re actively working to integrate all providers, but in the meantime, any providers that are not yet integrated will be blocked once the free-tier limit is reached.

If you have remaining credits, we estimate costs for providers that aren’t fully integrated with our billing system. These estimates are usually higher than the actual cost to prevent abuse, which is why PAYG is currently disabled for those providers.

You can track your spending on your billing page.

Routed requests vs direct calls

The documentation above assumes you are making routed requests to external providers. In practice, there are 3 different ways to run inference, each with unique billing implications:

• Routed Request: This is the default method for using Inference Providers. Simply use the JavaScript or Python InferenceClient, or make raw HTTP requests with your Hugging Face User Access Token. Your request is automatically routed through Hugging Face to the provider’s platform. No separate provider account is required, and billing is managed directly by Hugging Face. This approach lets you seamlessly switch between providers without additional setup.

• Routed Request with Custom Key: In your settings page on the Hub, you can configure a custom key for each provider. To use this option, you’ll need to create an account on the provider’s platform, and billing will be handled directly by that provider. Hugging Face won’t charge you for the call. This method gives you more control over billing when experimenting with models on the Hub. When making a routed request with a custom key, your code remains unchanged—you’ll still pass your Hugging Face User Access Token. Hugging Face will automatically swap the authentication when routing the request.

• Direct Calls: If you provide a custom key when using the JavaScript or Python InferenceClient, the call will be made directly to the provider’s platform. Billing is managed by the provider, and Hugging Face is not notified of the request. This option is ideal if you want to use the unified InferenceClient interface without routing through Hugging Face.

Here is a table that sums up what we’ve seen so far:

HF-Inference cost

As you may have noticed, you can select to work with "hf-inference" provider. This service used to be called “Inference API (serverless)” prior to Inference Providers. From a user point of view, working with HF Inference is the same as with any other provider. Past the free-tier credits, you get charged for every inference request based on the compute time x price of the underlying hardware.

For instance, a request to black-forest-labs/FLUX.1-dev that takes 10 seconds to complete on a GPU machine that costs $0.00012 per second to run, will be billed $0.0012.

The "hf-inference" provider is currently the default provider when working with the JavaScript and Python SDKs. Note that this default might change in the future.

Organization billing

For Enterprise Hub organizations, it is possible to centralize billing for all of your users. Each user still uses their own User Access Token but the requests are billed to your organization. This can be done by passing "X-HF-Bill-To: my-org-name" as a header in your HTTP requests.

Enterprise Hub organizations receive a pool of free usage credits based on the number of seats in the subscription. Inference Providers usage can be tracked on the organization’s billing page. Enterprise Hub organization administrators can also set a spending limit and disable a set of Inference Providers from the organization’s settings.

If you are using the JavaScript InferenceClient, you can set the billTo attribute at a client level:

import { InferenceClient } from "@huggingface/inference";

const client = new InferenceClient("hf_token", { billTo: "my-org-name" });

const image = await client.textToImage({
	model: "black-forest-labs/FLUX.1-schnell",
	inputs: "A majestic lion in a fantasy forest",
	provider: "fal-ai",
});
/// Use the generated image (it's a Blob)

And similarly in Python:

from huggingface_hub import InferenceClient
client = InferenceClient(provider="fal-ai", bill_to="my-org-name")
image = client.text_to_image(
    "A majestic lion in a fantasy forest",
    model="black-forest-labs/FLUX.1-schnell",
)
image.save("lion.png")