OpenAI Decisions API vs kettei

OpenAI Decisions API

Typed predicate, choice and score answers with probabilities, up to 200 questions a call, at $0.10 per million input tokens with no output charge. It is a public beta released on 6 October 2026, with one model alias, no dated snapshot, no Batch route and no SLA found.

kettei

OneHot returns probabilities for up to 128 typed questions a call at $0.02 to $0.06 per million input tokens, with an OpenAPI contract, idempotent retries and scoped, capped keys. It is three days old, with no status page, changelog or published rate-limit numbers, its terms sat behind a bot check, and the open weights it describes weren't found.

OpenAI Decisions API

1. Put independent questions about one input in a single questions array. Send a separate request when a question depends on an earlier answer
2. Check each answer's type before reading it. A question can come back as refusal while the others in the same request are answered
3. Send images as base64 data URLs, which the guide and the reference both accept. Hosted HTTP(S) URLs are accepted per the reference only, and file_id is rejected
4. Give a choice question a fallback value such as other, and set thresholds from your own labelled examples
5. Use Python SDK 3.26.0 or JavaScript 7.30.0 or later, and follow Retry-After on 429 and 503

kettei

1. Send context and decisions to POST https://api.sqwish.ai/v1/decide with a bearer key. Leaving out model gets kettei-core, which reads text only
2. Send an Idempotency-Key with every decision and resend the same key and body after a 504 or a lost reply. Replays aren't charged
3. Branch on error.code and error.retryable, not the status. Wait for Retry-After on 429 and retryable 503s
4. Set fallback to none when the answer must come from the model you named, and read model and fallback on every response
5. Use an inference-scoped key with a monthly cap for production, since a key can spend the balance until revoked