Topaz Image Upscale Generative API Documentation

Topaz Image Upscale Generative API Documentation

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Topaz Image Upscale Generative upscales and repairs images with Topaz’s generative Wonder, Recover and Redefine models. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Topaz Image Upscale Generative upscales and repairs images with Topaz’s generative Wonder, Recover and Redefine 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
    9 Topaz models, each tuned for a different kind of image.

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


Parameters

ParameterRequiredDescription
imageYesThe image to process (JPEG, PNG, TIFF or WebP).
modelNoThe Topaz model to use. Default: Wonder 4.
target_resolutionNoThe target resolution of the output: 2k (about 4 MP), 4k (about 16.8 MP) or 8k (about 67 MP). The source aspect ratio is preserved. Options: 2k, 4k, 8k. Default: 4k.
output_formatNoThe format of the output image. Options: jpeg, png. Default: jpeg.

Models

ModelBest for
Wonder 4The most advanced all-purpose generative enhancement and upscaling (default).
Wonder 3.5High-quality generative upscaling with great realism.
Wonder 3Generative realism for upscaling images.
Wonder 2Generative realism for challenging images.
WonderOne-click repair and enhancement of low to medium resolution images.
Recover 3Recovers rich detail in heavily degraded images.
Standard MAXHigh-quality upscaling with generative detail.
RedefineAdds new generative detail, guided by an automatic description.
DetailImproves realism in AI-generated faces.

Pricing

Wonder 4, Wonder 3.5 and Wonder 3: $0.10 at 2k, $0.30 at 4k, $0.90 at 8k. Wonder 2, Wonder, Recover 3, Standard MAX and Redefine: $0.20 at 2k, $0.50 at 4k, $1.70 at 8k. Detail: $0.10 at 2k and 4k, $0.30 at 8k.


How to Use

  1. Upload your image — Provide a URL or upload a file.
  2. Pick a model — Start with the default Wonder 4 and switch if your content needs it.
  3. Choose the target resolution — 2k, 4k, 8k.
  4. Submit — Download the result when it is ready.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "model": "Wonder 4",
  "target_resolution": "4k",
  "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/topaz/image/upscale-generative" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

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

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Retry temporary errors only while polling, never the submit request. Errors, retries and timeouts

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The image to process (JPEG, PNG, TIFF or WebP).
modelstringNoWonder 4Wonder 4, Wonder 3.5, Wonder 3, Wonder 2, Wonder, Recover 3, Standard MAX, Redefine, DetailThe Topaz model to use. Wonder 4: The most advanced all-purpose generative enhancement and upscaling (default). Wonder 3.5: High-quality generative upscaling with great realism. Wonder 3: Generative realism for upscaling images. Wonder 2: Generative realism for challenging images. Wonder: One-click repair and enhancement of low to medium resolution images. Recover 3: Recovers rich detail in heavily degraded images. Standard MAX: High-quality upscaling with generative detail. Redefine: Adds new generative detail, guided by an automatic description. Detail: Improves realism in AI-generated faces.
target_resolutionstringNo4k2k, 4k, 8kThe target resolution of the output: 2k (about 4 MP), 4k (about 16.8 MP) or 8k (about 67 MP). The source aspect ratio is preserved.
output_formatstringNojpegjpeg, pngThe format of the output image.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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