Celeris-1 Decision vs SPEV

Celeris-1 Decision

Typed probabilities, image inputs and optional explanations suit routing and classification inside an agent. Both System One and OpenAI Decisions request formats are documented. The service remains early access under its terms, activation can queue, and prepaid credit expires after 30 days. The published accuracy and latency figures are Celeris measurements, not Anchor Terminal tests.

SPEV

SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email.

Celeris-1 Decision

1. Use the decision model path and matching model field. This model has no chat, Responses or models endpoint.
2. Use at most 512 questions per request, or 64 with explanations. Both endpoints reject streaming.
3. Preserve x_celeris in a custom Jev SDK response model when reading explanations. The default response type drops it.
4. Retry 429 with Retry-After and backoff. Stop on 402 until workspace credit is replenished.
5. Read usage.input_tokens for cost, including images and request overhead. Track credit expiry separately from token consumption.

SPEV

1. Send model: "spev" to POST https://api.sprag.ai/v1/decisions with a bearer key. /v1/systemone returns 410
2. Ask every question about one piece of evidence in one request. Answers come back in question order
3. Send audio as base64 in input_audio with format, not as a data URL, and at most one image across all messages
4. Keep evidence and questions under 8,192 tokens. Over the limit returns 400 model_limit_exceeded
5. Back off on 429 and 503 for Retry-After seconds. Limits are 60 requests a minute per organisation by default
6. Handle an answer of type refusal, which carries no probabilities