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Data

Data as of October 13, 2026 · How the score is built

ScaleDown Classify

Decision readingScaleDown Classify is tracked, but not publicly ranked yet. The profile exposes 0 sourced benchmark rows and leaves unsupported fields blank until a published record exists.

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Release date not sourced · you are here

    ScaleDown Classify

    Not publicly ranked · $0.05 / $0

Base entry

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

Context window
1M tokens per request (provider-listed)ScaleDown model limits and pricing FAQ
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Output modalities
typed JSONScaleDown Decisions API documentation
Parameters
Not disclosed by the provider
Availability
ScaleDown API · Enterprise licensingScaleDown model limits and pricing FAQ
Cloud regions
Not tracked yet
Lifecycle
Tracked
API capabilities
POST /classify for user-defined labels and rubrics; POST /v1/scaledown for choice, noul, and score questions. Decisions input usage sums the internal call for each question.ScaleDown Decisions API documentation
Prompt caching
Not documented in the pricing recordScaleDown API pricing and FAQ
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

We track ScaleDown Classify, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.

ScaleDown Classify is a proprietary model with a 1M tokens per request (provider-listed) context window. No explicit reasoning mode is documented in this profile.

Available through the ScaleDown API. Enterprise licensing offers deployment on customer hardware; public downloadable weights are not listed. The provider lists a one-million-token request limit; an architectural configuration is not published.

ScaleDown Classify scores text against user-defined labels and rubrics, with single-label and multi-label modes. Its Jev-compatible Decisions endpoint answers choice, noul, and score questions using the same classifier. The documented model IDs are classify and classify-1. Decision requests bill input usage across the internal call for each question; use returned usage when estimating cost. Parameter count and exact launch date are not published in the reviewed sources. Task-specific provider results are not mapped into general benchmark scores.

The profile has no source-displayable benchmark row yet.

Last updated October 13, 2026. Runtime fields remain blank until a sourced snapshot exists.

Questions

How does ScaleDown Classify perform overall in AI benchmarks?

ScaleDown Classify does not have any source-displayable benchmark rows yet, so this profile does not assign a public score or rank. Documented specifications remain visible, while score-led charts and claims stay unavailable until a published evaluation can be attached to the exact model.

Does ScaleDown Classify have full benchmark coverage on BenchLM?

No. ScaleDown Classify currently has 0 source-displayable rows across 670 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of ScaleDown Classify?

ScaleDown Classify has a documented context window of 1M tokens per request (provider-listed). That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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