Hugging Face Inference Endpoints vs Lambda Cloud

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.

Lambda Cloud

H100 SXM at $3.99 and B200 at $6.69 an hour with per-minute billing. No scale to zero, autoscaling or endpoints; an idle VM bills until terminated.

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

Lambda Cloud

1. Call GET /instance-types first and read regions_with_capacity_available before trying to launch
2. Space launch calls 12 seconds apart; a sixth in a minute returns 429 with global/rate-limited
3. Branch on the error code, not the message or suggestion, which Lambda says may change
4. List instances before retrying a failed launch, since there's no idempotency key and a retry can start a second machine
5. Terminate the instance in a finally block; billing runs by the minute until you do