pplx-decider-flash vs ScaleDown

pplx-decider-flash

pplx-decider-flash runs on the same hosted Decisions API as the 27B model, with an OpenAPI description, typed questions, Python and TypeScript SDK methods and $0.01 per million input tokens, and its weights are public under Apache-2.0. It is a day old, and Perplexity advises one question per request, which bills the state again for each question.

ScaleDown

Classify answers Jev-shaped choice, noul and score questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.

pplx-decider-flash

1. Send Authorization: Bearer with model set to pplx-decider-flash-v1.2. A key in x-api-key returns 401.
2. Send one question per request by default. Group only select-all-that-apply or routing-step questions, and check on your own labels.
3. Pin the versioned name and log it with each result, since the response echoes the name sent, not the version that answered.
4. Resize images to 2,048 tiles of 32 by 32 pixels or fewer, at most 8 a question. Larger images end in a 504 after about a minute.
5. Compare it with pplx-decider-v1.2 on a labelled sample at your thresholds before choosing it.

ScaleDown

1. Send several questions about one item in one /v1/scaledown call. Each becomes its own Classify call and the usage is summed
2. Pin classify-1, extract-1 or summarize-1 once you've tuned thresholds on your own labelled cases
3. Set context_chars to 0 and use top_n on Extract unless you need the 500 characters of context each side
4. Set reasoning: false on /classify when you only need the label. The reasoning call bills its input at 2x
5. Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects