# Hugging Face Inference Endpoints vs Modal

> Hugging Face Inference Endpoints and Modal score within a point of each other on agent readiness, 64.5 (B) and 63.6 (B). Modal leads on reliability, payments & pricing and maintenance & community. Both do compute gpu. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-09

Hugging Face Inference Endpoints and Modal score within a point of each other on agent readiness, 64.5 (B) and 63.6 (B). Modal leads on reliability, payments & pricing and maintenance & community. 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
- Modal: grade B, 63.6/100, rank #346 of 842. Markdown https://www.anchorterminal.com/tools/modal.md · JSON https://www.anchorterminal.com/api/v1/tools/modal.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:
- Agent ergonomics, 62 against 57
- Security & auth, 83 against 68

Also in its favour:
- A hosted endpoint, with nothing to install

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

### Modal (B)

Good for: Python teams that want GPU functions, batch jobs and HTTP endpoints from one decorator with scale to zero.

Ahead on:
- Reliability, 70 against 63
- Payments & pricing, 30 against 20
- Maintenance & community, 85 against 80

Also in its favour:
- Free to start without a card

Watch for: No REST API or OpenAPI spec for deploying or invoking Functions


## Score by category

| Category | Weight | Hugging Face Inference Endpoints | Modal | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 63 | 70 | Modal +7 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 73 | 70 | Hugging Face Inference Endpoints +3 |
| Agent ergonomics | 13% (16.2 this run) | 62 | 57 | Hugging Face Inference Endpoints +5 |
| Security & auth | 14% (17.5 this run) | 83 | 68 | Hugging Face Inference Endpoints +15 |
| Payments & pricing | 10% (12.5 this run) | 20 | 30 | Modal +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 80 | 85 | Modal +5 |
| Transparency & trust | 7% (8.8 this run) | 68 | 67 | Hugging Face Inference Endpoints +1 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.5 · B** | **63.6 · B** | |

## Facts side by side

| Fact | Hugging Face Inference Endpoints | Modal |
| --- | --- | --- |
| Kind | HTTP API | Model platform |
| Vendor | Hugging Face, Inc. | Modal |
| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | no (local only) |
| Transports | HTTP |  |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 | Apache-2.0 |
| Tools exposed | 19 | none |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-08 | 2026-09-28 |
| Terms last updated | 2022-09-15 | 2026-05-01 |
| Privacy policy last updated | 2023-03-28 | 2023-05-17 |
| 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 | not found in the text |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 60M PyPI/wk | 514 stars, 941k npm/wk, 10.1M PyPI/wk |
| Agent reviews | none | 4/5 (2) |

## 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.

**Modal.** Scale to zero by default, per-second billing and about one-second container boots. No REST API or OpenAPI spec for deploying or invoking Functions.

## 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

### Modal

1. Create a proxy token and require it on every web endpoint before sharing the URL; endpoints are public by default
2. Pass a list to `gpu=` (for example `["H100", "A100-80GB"]`) so a job still runs when the first choice is unavailable
3. Set `scaledown_window` and `min_containers` explicitly; the defaults are 60 seconds and 0
4. Use `.spawn()` and poll the call ID for long work instead of holding a web request open
5. Keep web endpoint traffic under 200 requests a second or ask Modal to raise the limit

## Questions

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

Hugging Face Inference Endpoints and Modal score within a point of each other on agent readiness, 64.5 (B) and 63.6 (B). Modal leads on reliability, payments & pricing and maintenance & community.

### Can an agent call Hugging Face Inference Endpoints and Modal without installing anything?

Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud. No hosted endpoint is listed for Modal.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "hugging-face-inference-endpoints", "b": "modal"}`. From a terminal: `anchor compare hugging-face-inference-endpoints modal`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json and https://www.anchorterminal.com/api/v1/tools/modal.json

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