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ScaleDown: Extract

Source description (English)

Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through provider.options.scaledown.entities, and the...

View source on OpenRouter
Overview

Model specifications

Context
1,000,000 tokens
Maximum output
900,000 tokens
Architecture
text+image+file->text
Tokenizer
Other
Knowledge cutoff
Not provided
Moderated
No
OPENROUTER

Complete pricing

Synchronized OpenRouter rates. Token prices are shown per one million tokens.

Input
$0.04
per 1M tokens
Output
Free
per 1M tokens
API

Quick start

Set OPENROUTER_API_KEY locally. Python requires requests; JavaScript runs in Node.js. Keep the key on the server.

API documentation

curl --fail-with-body https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"scaledown/extract","messages":[{"role":"user","content":"Hello!"}]}'
Capabilities

Input → Output

Input
textimagefile
Output
text
API

Supported API parameters

max_tokens
Available providers

1 Provider

Checked: October 14, 2026

Live providers on OpenRouter

Provider availability, latency, throughput and routing can change continuously. Open the source page for current operational data.

OpenRouter

ScaleDown

Not provided
Context
1M
Maximum output
900K
Input
$0.04
Output
Free
Cache read
Not provided
Cache write
Not provided
scaledown

2 models

All models
scaledown logoscaledown

ScaleDown: Summarize

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...

Context
1M
Input
text · image · file
Output
text
Input: $0.04Output: Freeper 1M tokens
View model details →
scaledown logoscaledown

ScaleDown: Classify-1

Classify-1 is a structured decision model from ScaleDown, served through OpenRouter's Decisions API. It scores text or a document against caller-defined choice, yes/no, and ordered-scale questions and returns calibrated probabilities...

Context
1M
Input
text · image · file
Output
decisions
Input: $0.04 per 1M tokensOutput: Free per 1M tokens
View model details →