---
title: "Hugging Face Inference Providers free inference"
description: "$0.1 in credits refresh on a published schedule. See verified limits, model IDs, privacy terms, and primary sources for Hugging Face Inference Providers."
canonical_url: "https://freeinferencing.com/provider/huggingface_inference_providers/"
md_url: "https://freeinferencing.com/provider/huggingface_inference_providers.md"
last_updated: "2026-09-19"
---

# Hugging Face Inference Providers

> $0.1 in credits refresh on a published schedule.

## Classification

- **Directory:** Current
- **Free access:** Monthly credits
- **Status:** Available now
- **Confidence:** High
- **Payment card:** No
- **Account:** Required
- **Equivalent paid value:** $0.10/mo
- **API endpoint:** `https://router.huggingface.co/v1`

## Models mentioned

No stable model IDs were recorded in this snapshot.

## Limits and terms

```yaml
monthly_routed_credit_usd: 0.1
rate_limits: Provider and model specific.
overage: Purchased credits required after the monthly allowance.
caveat: BYOK calls do not consume Hugging Face monthly credits.
```

## What happens to your prompts?

**Partially private.** Hugging Face does not store routed bodies, but each selected upstream provider has its own independent data policy.

Privacy is audited separately from price. Review the current governing terms before sending sensitive or regulated data.

## Data governance and agreements

```yaml
data_governance:
  review_status: reviewed
  plan_scope: Hugging Face Inference Providers routing layer; each selected
    inference provider has separate data-security terms.
  prompt_retention: Hugging Face states it does not store request bodies or
    responses when routing requests. Debugging logs are kept up to 30 days
    without user data or tokens.
  response_retention: Hugging Face states routed responses are not stored.
  ordinary_logging: Debugging logs are retained up to 30 days but are described as
    excluding user data and tokens.
  model_training: Hugging Face states it does not store routed user data for
    training purposes; the selected upstream provider's separate policy still
    applies.
  product_improvement: No routed prompt or response use for Hugging Face training
    is disclosed; upstream provider policies must be reviewed separately.
  human_or_operator_access: Hugging Face says request and response bodies are not
    stored by its routing layer; upstream provider access remains
    provider-specific.
  subprocessors_and_routing: The service is a proxy that sends requests to the
    selected external inference provider, which is independently responsible for
    its security and data handling.
  deletion_controls: No routed content is said to be stored by Hugging Face;
    account personal-data rights are governed by the Hugging Face privacy
    policy.
  caveat: The Hugging Face proxy policy does not replace the policy of the final
    inference provider. Automatic routing can change which upstream processes a
    request.
agreements:
  terms_of_service: https://huggingface.co/terms-of-service
  privacy_policy: https://huggingface.co/privacy
```

## Eligibility

```yaml
account_required: true
payment_method_required: false
```

## API compatibility and modalities

- **Compatibility:** OpenAI Chat Completions, OpenAI Responses, OpenAI Models, Huggingface Sdk
- **Modalities:** Text generation


## Before you build with Hugging Face Inference Providers

### Read the classification narrowly

This record describes the bounded offer supported by evidence on 2026-09-19; it does not guarantee permanence, production suitability, uptime, latency, model quality, or access from every account and region. “Monthly credits” should be interpreted together with the Current directory placement, High confidence, No payment-card status, and the plan-specific sources below.

### Resolve the live model route

No stable model ID is recorded. Resolve the current machine-readable ID, endpoint, authentication method, and request shape from the provider's live documentation before writing fixed production configuration.

### Match the quota to the workload shape

Translate the allowance into peak requests per minute, input and output tokens, concurrency, retries, and every daily or monthly ceiling that applies to the intended account. The first limit reached by the workload is the practical ceiling. A large token pool can still fail interactive bursts, and a high request limit can still fail long-context work. Include tool calls and retry traffic, test the largest realistic payload, and treat research, experimental, and community access as conditional on their eligibility and fair-use terms.

### Preserve billing and privacy boundaries

The recorded payment-card requirement is No, and account access is required. Confirm both in the live signup flow, set provider-side budgets when charges are possible, and observe the balance or usage fields after a complete request. The prompt-handling classification is **Partially private** because Hugging Face does not store routed bodies, but each selected upstream provider has its own independent data policy. Re-read the terms for the exact route and plan before sending sensitive, regulated, or proprietary content.

### Follow the evidence, then re-check it

This record links 8 first-party sources covering the offer, catalog, limits, pricing, terms, privacy, or adoption evidence available to the audit. Prefer the newest and most specific governing document or live catalog when sources disagree. A dated finding can become stale even when the page remains online, so retain the source and snapshot that supported the decision and submit a correction when a provider changes a material term.

### Plan fallback without policy drift

A fallback should preserve modality, context length, streaming, structured output, tools, safety controls, and data terms, not only API syntax. Decide which errors may retry, cap retry storms, and prevent an exhausted free route from silently switching to a billable model. Rotating aliases and free pools can change behavior without changing the endpoint, so retain the response model field and test at least one substitute route before the primary offer becomes unavailable.

### Monitor the offer as a dependency

Capture the model ID, response model, rate-limit headers, usage fields, latency, HTTP status, and provider request identifier. Watch authorization failure, quota exhaustion, catalog removal, policy revision, and balance movement as separate failure modes. Re-check the live catalog and governing sources on a schedule proportionate to the workload's importance, and keep an owner and exit path for any production dependency on volatile free capacity.

### Test one complete request before scaling

Start with the smallest permitted request using the exact credential, model ID, endpoint, region, and account type intended for deployment. Record the status, headers, usage fields, response model, latency, and dashboard balance movement. Then exercise an invalid model, quota exhaustion, or rate limit so failure is explicit and cannot silently switch to a paid route. Validate streaming, structured output, and tool calls separately because a free model can expose fewer features than its paid counterpart. Keep a budget ceiling outside the application whenever billing is possible, and do not send sensitive data until the observed route matches the reviewed agreement.

## Primary sources

- [Pricing](https://huggingface.co/docs/inference-providers/main/en/pricing): Official Docs
- [Inference Providers overview](https://huggingface.co/docs/inference-providers/en/index): Official Docs
- [Inference Providers launch](https://huggingface.co/blog/inference-providers): Announcement
- [Terms of Service](https://huggingface.co/terms-of-service): Official Terms
- [Privacy Policy](https://huggingface.co/privacy): Official Privacy
- [Inference Providers Security and Compliance](https://huggingface.co/docs/inference-providers/security): Official Docs
- [State of Open Source on Hugging Face Spring 2026](https://huggingface.co/blog/huggingface/state-of-os-hf-spring-2026): Official Ecosystem Report
- [huggingface\_hub v1.0](https://huggingface.co/blog/huggingface-hub-v1): Official Changelog

## Sitemap

See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.