Topaz Image Upscale API Documentation
Playground
Try it on WaveSpeedAI!Topaz Image Upscale enlarges photos to 2K, 4K or 8K with precise, non-generative Topaz upscaling models. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Topaz Image Upscale enlarges photos to 2K, 4K or 8K with precise, non-generative Topaz upscaling 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
6 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
| Parameter | Required | Description |
|---|---|---|
| image | Yes | The image to process (JPEG, PNG, TIFF or WebP). |
| model | No | The Topaz model to use. Default: Standard V2. |
| target_resolution | No | The 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_format | No | The format of the output image. Options: jpeg, png. Default: jpeg. |
Models
| Model | Best for |
|---|---|
| Standard V2 | General-purpose upscaling balancing detail, sharpness and noise (default). |
| High Fidelity V2 | Faithful upscaling for high-quality sources. |
| Upscale High Fidelity V3 | Improved high-fidelity upscaling for high-resolution images. |
| Low Resolution V2 | Recovery-focused upscaling for small, low-resolution images. |
| CGI | Precise upscaling for artwork, illustrations and CG renders. |
| Text Refine | Clean upscaling for text, graphics and shapes. |
Pricing
2k: $0.10 per image. 4k: $0.10 per image. 8k: $0.30 per image.
How to Use
- Upload your image — Provide a URL or upload a file.
- Pick a model — Start with the default
Standard V2and switch if your content needs it. - Choose the target resolution —
2k,4k,8k. - Submit — Download the result when it is ready.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"model": "Standard V2",
"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" \
-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
doneRetry temporary errors only while polling, never the submit request. Errors, retries and timeouts
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| image | string | Yes | - | The image to process (JPEG, PNG, TIFF or WebP). | |
| model | string | No | Standard V2 | Standard V2, High Fidelity V2, Upscale High Fidelity V3, Low Resolution V2, CGI, Text Refine | The Topaz model to use. Standard V2: General-purpose upscaling balancing detail, sharpness and noise (default). High Fidelity V2: Faithful upscaling for high-quality sources. Upscale High Fidelity V3: Improved high-fidelity upscaling for high-resolution images. Low Resolution V2: Recovery-focused upscaling for small, low-resolution images. CGI: Precise upscaling for artwork, illustrations and CG renders. Text Refine: Clean upscaling for text, graphics and shapes. |
| target_resolution | string | No | 4k | 2k, 4k, 8k | The 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_format | string | No | jpeg | jpeg, png | The format of the output image. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Task status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses. |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<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.urls | object | Object containing related API endpoints |
| data.status | string | Status: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |