# Hugging Face Inference Endpoints vs Nebius AI Cloud

> Nebius AI Cloud scores 67.2 (B) on agent readiness against Hugging Face Inference Endpoints's 64.5 (B), and leads in 4 of 7 scored categories. Hugging Face Inference Endpoints leads on reliability. Both do compute gpu. Category scores, facts, verdicts and agent notes side by…

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Nebius AI Cloud scores 67.2 (B) on agent readiness against Hugging Face Inference Endpoints's 64.5 (B), and leads in 4 of 7 scored categories. Hugging Face Inference Endpoints leads on reliability. Both do compute gpu.

- Hugging Face Inference Endpoints: grade B, 64.5/100, rank #314 of 842. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json
- Nebius AI Cloud: grade B, 67.2/100, rank #240 of 842. Markdown https://www.anchorterminal.com/tools/nebius-ai-cloud.md · JSON https://www.anchorterminal.com/api/v1/tools/nebius-ai-cloud.json

## Which one, for what

### Hugging Face Inference Endpoints (B)

Good for: Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.

Ahead on:
- Reliability, 63 against 57

Watch for: No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running

### Nebius AI Cloud (B)

Good for: Teams that want whole GPU VMs or InfiniBand clusters in Europe, the UK, Israel or the US with IAM, Terraform and an SLA, and are content to manage endpoint lifecycles themselves.

Ahead on:
- Schema & documentation, 78 against 73
- Agent ergonomics, 77 against 62
- Transparency & trust, 77 against 68

Also in its favour:
- Runs on your own machine

Watch for: Status page lists 14 incidents marked major between 14 July and 8 October 2026, including about 21 hours of partial degradation in us-central1 on 19 August


## Score by category

| Category | Weight | Hugging Face Inference Endpoints | Nebius AI Cloud | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 63 | 57 | Hugging Face Inference Endpoints +6 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 73 | 78 | Nebius AI Cloud +5 |
| Agent ergonomics | 13% (16.2 this run) | 62 | 77 | Nebius AI Cloud +15 |
| Security & auth | 14% (17.5 this run) | 83 | 81 | Hugging Face Inference Endpoints +2 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 80 | 82 | Nebius AI Cloud +2 |
| Transparency & trust | 7% (8.8 this run) | 68 | 77 | Nebius AI Cloud +9 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.5 · B** | **67.2 · B** | |

## Facts side by side

| Fact | Hugging Face Inference Endpoints | Nebius AI Cloud |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Hugging Face, Inc. | Nebius |
| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | `https://api.nebius.cloud` |
| Transports | HTTP | HTTP, stdio |
| Auth | OAuth or key | OAuth or key |
| Pricing | Pay per use | Pay per use |
| Price for compute gpu | not published | $1.35 per GPU-hour |
| x402 | no | no |
| Licence | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 | Proprietary service under the Nebius Services Agreement. The API definitions, the Go, Python and JavaScript SDKs and the MCP server on GitHub are MIT |
| Tools exposed | 19 | none |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-08 | 2026-10-07 |
| Terms last updated | 2022-09-15 | 2026-09-28 |
| Privacy policy last updated | 2023-03-28 | 2026-09-23 |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 60M PyPI/wk | 4.1k npm/wk, 469k PyPI/wk |

## Verdicts

**Hugging Face Inference Endpoints.** OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.

**Nebius AI Cloud.** One API definition generates the REST and gRPC interfaces, the CLI, Terraform provider and three SDKs, with a 602-operation OpenAPI document, `X-Idempotency-Key` and role-scoped service accounts. The status page lists 14 major incidents between 14 July and 8 October 2026, no request rate limits were found, and signup needs a browser and a card.

## Before you call either

### Hugging Face Inference Endpoints

1. Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available
2. Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts
3. Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes
4. Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running
5. Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer

### Nebius AI Cloud

1. Use a service account with an authorised key, then exchange a five-minute RS256 JWT at `https://auth.eu.nebius.com/oauth2/token/exchange` for a 12-hour Bearer token
2. Send `X-Idempotency-Key` with a random UUID on every create, update and delete, since a 504 can follow a call that succeeded
3. Poll the returned operation (`/ai/v1/endpoints/operations/{id}`) until `status` is set; concurrent operations on one resource are not supported
4. Stop or delete endpoints when idle. A stopped endpoint bills nothing, a stopped Devlab or VM still bills for its disk
5. Check region support first. Serverless AI is absent from `eu-south1` and `us-north1`, and each GPU platform exists in one to four regions
6. Run the beta `nebius/mcp-server` with safe mode on (the default); `nebius_cli_execute` can run any CLI command when `SAFE_MODE=false`

## Questions

### Which is better for AI agents, Hugging Face Inference Endpoints or Nebius AI Cloud?

Nebius AI Cloud scores 67.2 (B) on agent readiness against Hugging Face Inference Endpoints's 64.5 (B), and leads in 4 of 7 scored categories. Hugging Face Inference Endpoints leads on reliability.

### Do Hugging Face Inference Endpoints and Nebius AI Cloud need an API key?

Both take an API key or an OAuth sign-in.

### Can an agent call Hugging Face Inference Endpoints and Nebius AI Cloud without installing anything?

Yes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Nebius AI Cloud at https://api.nebius.cloud.


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