Real-ESRGAN delivers high-quality image super-resolution with optional face correction and adjustable upscale factors. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.0024per run·~416 / $1










Real-ESRGAN is an image upscaling and enhancement model that improves resolution and perceived detail while keeping the original content intact. Upload a low-resolution or slightly blurry image and the model produces a sharper, higher-quality result suitable for publishing, sharing, or downstream generation workflows. It’s commonly used as a final polish step for portraits, product photos, and AI-generated images.
| Output | Price |
|---|---|
| Per upscaled image | $0.0024 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/real-esrgan with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Real Esrgan below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/real-esrgan" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"image": "https://example.com/your-input.jpg"
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/real-esrgan", {
"image": "https://example.com/your-input.jpg"
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/real-esrgan",
{
"image": "https://example.com/your-input.jpg"
}
)
print(output["outputs"][0]) # → URL of the generated outputReal Esrgan is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. Real-ESRGAN delivers high-quality image super-resolution with optional face correction and adjustable upscale factors. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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 prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/real-esrgan.
Real Esrgan starts at $0.002 per run. 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.
Key inputs: `image`. 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/wavespeed-ai/real-esrgan.
Average end-to-end generation time on WaveSpeedAI is around 13 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.