Image by Topaz

Topaz Image Upscale API

Photo and forensic upscaler — best for realistic content.

Integrate Topaz Image Upscale with a single API call — one key, one unified endpoint, and shared billing across every model on Apiframe.

Get API Key View Docs

model: "topaz-image-upscale"

What's special about Topaz Image Upscale

Image-to-image editing and reference-image support.
Fast turnaround — about 30s per generation on average.
Pay-as-you-go pricing with no Topaz account required — you only pay for successful generations.
One API key, unified billing, idempotency and webhooks across every Apiframe model.

Made with Topaz Image Upscale

A few outputs generated through the Topaz Image Upscale API on Apiframe.

Sample coming soon

Overview

Endpoint: POST /v2/images/upscale
Model ID: topaz-image-upscale
Params key: topazUpscaleParams
Modality: image
Provider: Topaz
Pricing: Pay-as-you-go
Avg. completion: ~30s

Capabilities

Image inputSupported

Avg. time~30s

Quick start

Send a single POST /v2/images/upscale request with your API key to generate with Topaz Image Upscale. The call returns a jobId you can poll or receive via webhook.

curl -X POST https://api.apiframe.ai/v2/images/upscale \
  -H "X-API-Key: afk_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
        "model": "topaz-image-upscale",
        "topazUpscaleParams": {
            "image": "https://example.com/input.jpg",
            "upscale_factor": "2",
            "model_type": "standard-v2",
            "face_enhance": false
        }
    }'

import requests

response = requests.post(
    "https://api.apiframe.ai/v2/images/upscale",
    headers={
        "X-API-Key": "afk_your_api_key_here",
        "Content-Type": "application/json",
    },
    json={
        "model": "topaz-image-upscale",
        "topazUpscaleParams": {
            "image": "https://example.com/input.jpg",
            "upscale_factor": "2",
            "model_type": "standard-v2",
            "face_enhance": False
        }
    },
)
print(response.json())  # { "jobId": "...", "status": "QUEUED" }

const response = await fetch("https://api.apiframe.ai/v2/images/upscale", {
  method: "POST",
  headers: {
    "X-API-Key": "afk_your_api_key_here",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "topaz-image-upscale",
    "topazUpscaleParams": {
      "image": "https://example.com/input.jpg",
      "upscale_factor": "2",
      "model_type": "standard-v2",
      "face_enhance": false
    }
  }),
});
const { jobId } = await response.json();
console.log(jobId);

Response & job lifecycle

Generation is asynchronous. A successful submission returns 202 Accepted with a jobId. Poll GET /v2/jobs/{id} (or supply a webhook_url) until the status is COMPLETED; the result field then holds the output URL(s).

1. Submission response (202)

{
  "jobId": "b2c3d4e5-f6a7-8901-bcde-f23456789012",
  "status": "QUEUED"
}

2. Poll for the result

curl https://api.apiframe.ai/v2/jobs/JOB_ID \
  -H "X-API-Key: afk_your_api_key_here"

import requests, time

while True:
    job = requests.get(
        "https://api.apiframe.ai/v2/jobs/JOB_ID",
        headers={"X-API-Key": "afk_your_api_key_here"},
    ).json()
    if job["status"] in ("COMPLETED", "FAILED"):
        break
    time.sleep(2)
print(job["result"])

let job;
do {
  await new Promise((r) => setTimeout(r, 2000));
  job = await fetch("https://api.apiframe.ai/v2/jobs/JOB_ID", {
    headers: { "X-API-Key": "afk_your_api_key_here" },
  }).then((r) => r.json());
} while (job.status !== "COMPLETED" && job.status !== "FAILED");
console.log(job.result);

Input schema

Request parameters accepted by the Topaz Image Upscale endpoint. Model-specific options are nested under the params object shown below.

Parameter	Type	Required	Default	Allowed / range	Description
model	string	required	"topaz-image-upscale"	"topaz-image-upscale"	The model identifier for this endpoint.
topazUpscaleParams.image	string (URL)	optional	—	—	The image to upscale.
topazUpscaleParams.upscale_factor	string	optional	"2"	"1", "2", "4", "6"	Upscale factor
topazUpscaleParams.model_type	string	optional	"standard-v2"	"standard-v2", "low-res-v2", "cgi", "high-fidelity-v2", "text-refine", "redefine"	Enhancement model
topazUpscaleParams.face_enhance	boolean	optional	false	—	Recover facial detail in portraits.
topazUpscaleParams.face_enhance_strength	number	optional	0.8	min 0, max 1, step 0.05	Face strength
topazUpscaleParams.face_enhance_creativity	number	optional	0	min 0, max 1, step 0.05	Face creativity
topazUpscaleParams.output_format	string	optional	"jpg"	"jpg", "png"	Output format
topazUpscaleParams.seed	number	optional	—	step 1	Reuse a number to reproduce the same result.

Frequently Asked Questions

Common questions about the Topaz Image Upscale API.

Is there an API for Topaz Image Upscale?

Yes. Apiframe exposes Topaz Image Upscale through a single REST endpoint (`POST /v2/images/upscale` with `model: "topaz-image-upscale"`). You get one unified API, key, and billing across every supported model — no separate Topaz account required.

How much does the Topaz Image Upscale API cost?

Topaz Image Upscale uses simple pay-as-you-go pricing on Apiframe — you only pay for successful generations. See the pricing page for plans and volume discounts.

How do I call the Topaz Image Upscale API?

Send a POST request to `/v2/images/upscale` with your `X-API-Key` and a JSON body containing `model: "topaz-image-upscale"`. The call returns a `jobId`; poll `GET /v2/jobs/{id}` or use a webhook to receive the result.

What parameters does Topaz Image Upscale support?

Topaz Image Upscale accepts 8 model-specific parameters (nested under `topazUpscaleParams`) plus the common `prompt` and `webhook_url` fields. See the input schema above for the full list with types and defaults.

Still have questions?

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Start building with the Topaz Image Upscale API

Get your API key and integrate Topaz Image Upscale in minutes — Pay-as-you-go.

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One API for every model

Webhooks, SDKs & idempotency

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