Topaz Video Upscale API

topaz/video/upscale

Topaz Video Upscale upscales and enhances video up to 4K with Topaz's precision Proteus, Artemis, Gaia, Theia, Iris and Dione models. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Upscale Video
Input

Drag & drop or click to upload

Idle

topaz/video/upscale preview unavailable

$0.1per run·~10 / $1

Related Models

README

Topaz Video Upscale

Topaz Video Upscale upscales and enhances video up to 4K with Topaz's precision Proteus, Artemis, Gaia, Theia, Iris and Dione models, powered by Topaz Labs models.

Why Choose This?

  • Professional Topaz quality
    The same models used by photographers, filmmakers and studios.

  • Choose the right model
    21 Topaz models, each tuned for a different kind of video.

  • Pay for what you process
    Pricing follows the size of the output, matching Topaz's own rates.

Parameters

ParameterRequiredDescription
videoYesThe video to process.
modelNoThe Topaz model to use. Default: Proteus.
target_resolutionNoTarget resolution to upscale to. The source aspect ratio is preserved. Options: 720p, 1080p, 2k, 4k. Default: 1080p.

Models

ModelBest for
ProteusThe default choice for video enhancement and upscaling (default).
Proteus NaturalNext-generation natural enhancement; always upscales 2x.
RheaHigh-fidelity upscaling for fine detail.
Artemis High QualityEnhancement for high-quality sources.
Artemis Medium QualityBalanced enhancement for medium-quality footage.
Artemis Low QualityHeavier restoration for low-quality footage.
Artemis Medium HaloRemoves moderate edge haloing.
Artemis Strong HaloRemoves pronounced edge haloing.
Artemis Aliasing & MoireReduces aliasing and moire.
Gaia High QualityFine detail for already-clean sources.
Gaia CGUpscaling for animation, CG and stylized footage.
Gaia 2 AnimationAnimation upscaling; always upscales 2x.
Theia Fine Tune DetailAggressive per-frame detail enhancement.
Theia Fine Tune FidelityStable, consistent detail with high fidelity.
Iris Medium QualityFace recovery for mid-quality footage.
Iris Low QualityFace recovery for degraded footage.
Dione DVDeinterlacing for DV sources.
Dione TVDeinterlacing for TV sources.
Dione RobustDeinterlacing for challenging interlaced content.
Dione DehaloDeinterlacing plus halo removal.
Dione Robust DehaloRobust deinterlacing plus halo removal.

Pricing

$0.20 per gigapixel processed, where gigapixels = (width × step) × (height × step) × frames ÷ 1024³ and the step is 1 for a scale up to 1.2x, 2 up to 2.4x and 4 above. Gaia 2 Animation: $0.10 per 300 frames up to 1080p output, per 100 frames above. Minimum $0.10.

How to Use

  1. Upload your video — Provide a URL or upload a file.
  2. Pick a model — Start with the default Proteus and switch if your content needs it.
  3. Choose the target resolution — 720p, 1080p, 2k, 4k.
  4. Submit — Download the result when it is ready.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Video Upscale API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/topaz/video/upscale with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Video Upscale below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "model": "Proteus",
    "target_resolution": "1080p"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/topaz/video/upscale" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/topaz/video/upscale";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
        "model": "Proteus",
        "target_resolution": "1080p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "model": "Proteus",
    "target_resolution": "1080p"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/topaz/video/upscale", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Video Upscale API — Frequently asked questions

What is the Video Upscale API?

Video Upscale is a Topaz model for video upscaling, exposed as a REST API on WaveSpeedAI. Topaz Video Upscale upscales and enhances video up to 4K with Topaz's precision Proteus, Artemis, Gaia, Theia, Iris and Dione models. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Video Upscale API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/topaz/topaz-video-upscale.

How much does Video Upscale cost per run or per second?

Video Upscale starts at $0.1 per run or per second. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Video Upscale accept?

Key inputs: `video`, `model`, `target_resolution`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/topaz/topaz-video-upscale.

How do I get started with the Video Upscale API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Video Upscale outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Topaz). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — topaz/video/upscale for AI agents and LLMs