Celeris-1 Decision vs Decider

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.

Decider

An Apache-2.0 decision model family with a dated changelog, passing CI, 21 package releases since 22 September 2026 and model cards that list measured regressions. One person maintains it, the local server has no authentication option, states over 32,768 tokens are cut without an error, and no security policy is published.

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.

Decider

1. Pin weights by Hub tag (v10, v2) when results must repeat. The main branch of each model repository changes with new versions
2. Read x_p_max for the top probability. Since 1.3.0 confidence on choice and score answers follows TypeSafe's rescaled definition, not the top probability
3. Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option
4. Count state tokens before sending. Over 32,768 the state is cut silently, and /decide caps context at 1,536 tokens
5. Split multi-step arithmetic or multi-hop judgements into several questions, and don't write long rules into a question. The README says both fail