Pricing and Billing

Access 200+ models from leading AI inference providers with centralized, transparent, pay-as-you-go pricing. No infrastructure management required—just pay for what you use, with no markup from Hugging Face.

Free Credits to Get Started

Every Hugging Face user receives monthly credits to experiment with Inference Providers:

How Billing Works: Choose Your Approach

Inference Providers offers flexibility in how you’re billed. Understanding these options upfront helps you choose the best approach for your needs:

Which Option Should I Choose?

• Start with Routed by Hugging Face if you want simplicity and to use your monthly credits
• Use Custom Provider Key if you need specific provider features or you’re consistently using the same provider

Pay-as-you-Go Details

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.

PRO users and Enterprise Hub organizations can continue using the API after exhausting their monthly credits. This ensures uninterrupted access to models for production workloads.

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 anytime on your billing page.

Hugging Face Billing vs Custom Provider Key (Detailed Comparison)

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:

• Hugging Face Routed Requests: 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.

• Custom Provider Key: You can bring your own provider key to use with the Inference Providers. This is useful if you already have an account with a provider and you want to use it with the Inference Providers. Hugging Face won’t charge you for the call.

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.

Billing for Team and Enterprise organizations

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")