scaledown

ScaleDown: Summarize

scaledown/summarize

Our take

AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.

OpenRouter’s catalog describes scaledown/summarize as a ScaleDown abstractive summarization model that rewrites long text and documents fluently rather than extracting source sentences. The listing reports text, image, and file inputs with text output, a very large context window, and max_tokens output control. This evidence is catalog-only: no independent model card or measured benchmark results were supplied, so real-world fidelity and multimodal behavior require workload validation.[1]

Strengths

Catalog-reported abstractive rewriting aims for fluent, faithful summaries rather than sentence extraction.[1]
The listing reports text, image, and file inputs with text output.[1]
A very large advertised context window and max_tokens support may suit long inputs and controlled output length.[1]

Limitations

Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack.[1]
No measured benchmark results or evaluation data were provided, so summarization quality is unverified.[1]
Knowledge cutoff and broader generation controls are not documented; faithful and multimodal behavior should be validated on target workloads.[1]

Where to use it

Potentially useful for condensing long articles, reports, and document collections.[1]
Could be evaluated for workflows that summarize mixed text, image, and file inputs.[1]
May fit pilots that need concise summaries with explicit output-length limits.[1]

Sources

[1] OpenRouter catalog · ScaleDown: SummarizeSources checked: Nov 13, 2026

About this model

Description below is the original text supplied by OpenRouter, shown in the source language.

Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...

Specifications

Model ID: scaledown/summarize
Canonical ID: scaledown/summarize-20260928
Creator: scaledown
Added to OpenRouter: 13.10.2026
Context length: 1,000,000
Modality: text+image+file->text
Input modalities: text, image, file
Output modalities: text
Token pricing: USD per 1M tokens: in $0.040 / out $0
Knowledge cutoff: —
Expiration date: —

Tasks and capabilities

A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.

Task	Grade	Source-declared capability
General quality	No measurement	—
Coding	No measurement	—
Agents	No measurement	—
Writing	No measurement	output: text
Reasoning	No measurement	—
Document analysis	No measurement	input: file
Vision	No measurement	input: image
Image generation	No measurement	—
Audio	No measurement	—
Video	No measurement	—
Embeddings	No measurement	—

Evaluations

No evaluations are supplied for this model.

How grades work

Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.

S — S — top 10% of the cohort
A — A — next 20% of the cohort
B — B — next 30% of the cohort
C — C — below the B band

Providers

Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.

Provider	Context length	Price in /1M	Price out /1M	Latency p50 (30m, s)	Throughput p50 (30m, tok/s)	Uptime (30m)
ScaleDown	1,000,000	$0.040	$0	—	—	100%

Provider data retrieved: 13.11.2026

No published articles identify this model yet.