Cerebrium vs Modal

Cerebrium

Per-second GPU prices are public, a 94-operation OpenAPI spec covers the management API, and service account tokens expire and are limited to named projects. Deployed endpoints are callable without a token unless disable_auth = false is set, and no request rate limits, 429 handling or SLA were found in the reviewed documentation.

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.

Cerebrium

1. Set disable_auth = false in cerebrium.toml before deploying. The default leaves the endpoint callable by anyone with the URL
2. Authenticate headless with CEREBRIUM_SERVICE_ACCOUNT_TOKEN. cerebrium login opens a browser
3. Raise response_grace_period for long work. It defaults to 15 minutes and async runs stop at 12 hours
4. Send ?async=true to get a run_id with HTTP 202, and add webhookEndpoint because async calls return no result to the caller
5. Check the plan before choosing hardware. A100, H100, H200, B200 and RTX PRO 6000 need Standard, and protected compute bills at twice the listed rate

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