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Inference Endpoints

Is Hugging Face Inference Endpoints down? Live status

Dedicated GPU inference on AWS/Azure/GCP

Live status for Hugging Face Inference Endpoints — the dedicated GPU deployment control-plane at api.endpoints.huggingface.cloud.

Inference Endpoints API Status

Live, in-browser checks against Inference Endpoints's public APIs. Refreshes every 15s.

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Control plane

Endpoints API and dashboard

2 endpoints
  • Dashboard
    ui.endpoints.huggingface.cloud
    —ms
    warming up
  • Endpoints API
    api.endpoints.huggingface.cloud
    —ms
    warming up
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Individual endpoint URLs are per-tenant and can't be probed from a public dashboard. These checks confirm reachability of the shared control plane.

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About Inference Endpoints

Inference Endpoints let you deploy any model from the Hub onto dedicated GPU or CPU instances across AWS, Azure, and GCP — with autoscaling, scale-to-zero, and per-second billing. This page tracks the shared control plane.

Inference Endpoints at a glance

Clouds
AWS, Azure, GCP
Billing
Per-second, per-instance
Scale-to-zero
Optional idle sleep
Model source
Any Hub model
Best for
Production, predictable latency

Common Inference Endpoints issues

  • Cold-start on first request

    Scale-to-zero endpoints must load model weights before serving. Large LLMs take 60–180s. Turn off scale-to-zero for latency-sensitive traffic.

  • GPU capacity error at deploy

    Some GPU SKUs (A100, H100) have limited regional capacity. Try a different region or downshift to L4/A10G if latency budget allows.

  • Quota exceeded on the org

    Orgs have vCPU/GPU quotas. Request an increase from the Endpoints dashboard — approvals for standard SKUs are usually fast.

Background

Hugging Face launched Inference Endpoints in 2022 to give teams a one-click path from a Hub model card to a production-ready HTTPS endpoint. It sits alongside the Serverless Inference API and the newer OpenAI-compatible router as the paid, dedicated tier.

Frequently asked

What's the difference from the Serverless Inference API?
Serverless Inference is a shared pool — free, rate-limited, cold-starts on load. Inference Endpoints are dedicated instances you provision, sized for your model, with predictable latency and per-second billing.
How does scale-to-zero work?
Endpoints can be configured to sleep after N minutes of idle. The next request cold-starts the instance — expect 30s–2min depending on model size and cloud region.

About this check

All data is provided on a best-effort basis with no guarantees about accuracy or availability. This is an unofficial status page and is not affiliated with, endorsed by, or sponsored by Hugging Face, Inc.

Checks run client-side from your browser against Inference Endpoints's public endpoints. Latency reflects your network path, not the server's health alone. See our resources for more on how to read these checks.

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