pplx-decider vs SPEV

pplx-decider

The hosted Decisions API has an OpenAPI description, typed questions, documented limits and a published price of $0.02 per million input tokens, and the v1.1 weights are public under Apache-2.0. The API is days old, the official Python SDK has no method for it, and the governing terms and privacy notice could not be read on 9 October 2026.

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.

pplx-decider

1. Send Authorization: Bearer. A key in x-api-key returns 401 on this endpoint.
2. Set model on every request. A missing or unknown model returns 400, and the guide shows a -latest name rejected.
3. Resize images to 2,048 tiles of 32 by 32 pixels or fewer before sending. Larger images end in a 504 after about a minute.
4. Check the HTTP status before parsing an error. 404 and 405 have empty bodies, 504 can be HTML, and error.code changes type.
5. For the weights, use the repository's autojev code. The card says default causal inference does not reproduce the evaluated setup.

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