scaledown-extract
ScaleDown Extract is a document extraction model. It needs provider.options.scaledown.entities in the request to specify the entities to extract.
Pricing: Input 9.6 credits / 1M tokens (≈ $0.05), Output 0 credits / 1M tokens (≈ $0.00).
How can I help you today?
This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.
More AI models from ScaleDown
Latest and popular AI models
Extract API on ModelFold
ScaleDown Extract is a document extraction model. It needs provider.options.scaledown.entities in the request to specify the entities to extract. Try Extract in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Extract API
Extract at a glance
Extract is a chat model from ScaleDown. It accepts text, images and files (such as PDF) as input and returns text, with a context window of up to 1M tokens.
Use it without hosting anything
On ModelFold you call Extract with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Extract
Up to 1M tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Understands images and files (such as PDF)
Besides text, Extract accepts images and files (such as PDF) as input, so a single request can combine instructions with visual or other media.
How to Use Extract on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Extract responds before writing any code.
- 2
Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "scaledown-extract" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Extract
Long-document workflows
Feed in long reports, contracts, manuals or codebases and ask for summaries, comparisons and answers grounded in the material.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Frequently Asked Questions
What is Extract?⌄
ScaleDown Extract is a document extraction model. It needs provider.options.scaledown.entities in the request to specify the entities to extract.
Which inputs does Extract support?⌄
Extract accepts text, images and files (such as PDF) and returns text. Through ModelFold you can send text and images (OpenAI-style image_url content); in the Playground you can also attach documents, which are converted to text.
How long is the context window of Extract?⌄
Up to 1M tokens, shared between your input and the model’s output.
Does Extract support function calling?⌄
Function calling is not listed for Extract; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Extract billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Extract through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "scaledown-extract", using your ModelFold API key as the Bearer token.
| Input | 9.6 credits 1M tokens≈ $0.05 |
| Output | 0 credits 1M tokens≈ $0.00 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"scaledown-extract","messages":[{"role":"user","content":"Hello"}]}'

