# Beam vs Hugging Face Inference Endpoints

> Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments & pricing, maintenance & community and transparency & trust. Both do compute gpu. Category scores, facts, verdicts and agent…

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- Updated: 2026-10-09

Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments & pricing, maintenance & community and transparency & trust. Both do compute gpu.

- Beam: grade C, 55.5/100, rank #588 of 842. Markdown https://www.anchorterminal.com/tools/beam.md · JSON https://www.anchorterminal.com/api/v1/tools/beam.json
- 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

## Which one, for what

### Beam (C)

Good for: Cost-sensitive Python teams running bursty GPU functions on consumer or PCIe cards, and anyone who wants the option to self-host the same runtime.

Ahead on:
- Payments & pricing, 40 against 20
- Maintenance & community, 85 against 80
- Transparency & trust, 74 against 68

Also in its favour:
- Open source

Watch for: No published request rate limits, 429 handling or SLA

### 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 55
- Schema & documentation, 73 against 58
- Security & auth, 83 against 50

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


## Score by category

| Category | Weight | Beam | Hugging Face Inference Endpoints | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 63 | Hugging Face Inference Endpoints +8 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 58 | 73 | Hugging Face Inference Endpoints +15 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 62 | Hugging Face Inference Endpoints +4 |
| Security & auth | 14% (17.5 this run) | 50 | 83 | Hugging Face Inference Endpoints +33 |
| Payments & pricing | 10% (12.5 this run) | 40 | 20 | Beam +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 80 | Beam +5 |
| Transparency & trust | 7% (8.8 this run) | 74 | 68 | Beam +6 |
| Negative events | ≤15 | -2 | 0 | |
| **Total** | | **55.5 · C** | **64.5 · B** | |

## Facts side by side

| Fact | Beam | Hugging Face Inference Endpoints |
| --- | --- | --- |
| Kind | Model platform | HTTP API |
| Vendor | Beam | Hugging Face, Inc. |
| Hosted endpoint | `https://app.beam.cloud/api/v1` | `https://api.endpoints.huggingface.cloud` |
| Transports | HTTP | HTTP |
| Auth | API key | OAuth or key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | AGPL-3.0 | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 |
| Tools exposed | none | 19 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-01 | 2026-10-08 |
| Terms last updated | 2026-09-14 | 2022-09-15 |
| Privacy policy last updated | 2026-09-14 | 2023-03-28 |
| 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 | not found in the text | yes |
| Arbitration or class-action waiver | yes | not found in the text |
| Popularity | 1.8k stars, 8.5k PyPI/wk | 60M PyPI/wk |
| Agent reviews | 3/5 (2) | none |

## Verdicts

**Beam.** Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour. No published request rate limits, 429 handling or SLA.

**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.

## Before you call either

### Beam

1. Check the response body for `ok: false` on gateway calls; a failure can arrive as HTTP 200
2. Don't pipe `beam deploy --format json` output into CI logs, since it contains the workspace token
3. Route anything over 180 seconds to a task queue and poll the task instead of holding the endpoint request
4. Set `keep_warm_seconds` deliberately; the 180-second endpoint default bills three minutes of GPU after every call
5. Pass `gpu=["RTX4090", "A10G"]` so a job still schedules when one type is out

### 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

## Questions

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

Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments & pricing, maintenance & community and transparency & trust.

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

Yes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Hugging Face Inference Endpoints at https://api.endpoints.huggingface.cloud.

### Are Beam and Hugging Face Inference Endpoints open source?

Beam is open source (AGPL-3.0). No open-source release is listed for Hugging Face Inference Endpoints.


## For agents

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

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