Image to SVG

Convert a raster image (PNG, JPEG, WebP) into SVG via POST /v1/svgs/vectorizations. Examples below use arrow-preview. To discover model IDs available to your organization, call GET /v1/models. Set stream: true to receive reasoning, draft, and content Server-Sent Events while the SVG is being produced.

Example

Node.js SDK
cURL

import { QuiverAI } from "@quiverai/sdk";

const client = new QuiverAI({
  bearerAuth: process.env["QUIVERAI_API_KEY"],
});

const result = await client.vectorizeSVG.vectorizeSVG({
  model: "arrow-preview",
  autoCrop: true,
  image: {
    url: "https://example.com/logo.png",
  },
});

curl --request POST \
  --url https://api.quiver.ai/v1/svgs/vectorizations \
  --header 'Authorization: Bearer <QUIVERAI_API_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "arrow-preview",
    "auto_crop": true,
    "image": {
      "url": "https://example.com/logo.png"
    }
  }'

Preparing the image

Cropping the input image tightly to the subject usually improves output quality. Use auto_crop as a fallback when you can’t crop manually.

Parameters

Parameter	Type	Default	Description
`model`	string	—	Required. Model identifier (for example, `arrow-preview`).
`image`	object	—	Required. Input image as `{ url: "..." }` or `{ base64: "..." }`.
`auto_crop`	boolean	`false`	Automatically crop the image to the dominant subject before vectorization.
`target_size`	integer	—	Square resize target in pixels (128 to 4096).
`stream`	boolean	`false`	When `true`, returns a Server-Sent Events stream with progressive rendering phases (`reasoning`, `draft`, `content`).
`temperature`	number	`1`	Controls randomness (0 to 2). Lower values produce more deterministic output; higher values increase variety.
`top_p`	number	`1`	Nucleus sampling (0 to 1). Limits token selection to the smallest set whose cumulative probability exceeds this value. Lower values make output more focused.
`presence_penalty`	number	`0`	Penalizes tokens already present in prior output (-2 to 2). Positive values encourage the model to explore new patterns.
`max_output_tokens`	integer	—	Upper bound for output token count (1 to 131072).

Get started

Guides

Models

Example

Preparing the image

Parameters

Get started

Guides

Models

​Example

​Preparing the image

​Parameters

Example

Preparing the image

Parameters