xAI Grok Imagine Image Quality Edit is a fast AI image editing model that edits and enhances images with high-quality visual output using a dedicated RunPod workflow. Ready-to-use REST inference API for photo retouching, creative image edits, product image enhancement, marketing assets, social media visuals, and professional AI image editing workflows with simple integration, no coldstarts, and affordable pricing.
Idle

$0.07per run·~14 / $1

Add a faint handwritten chalk message on the old blackboard: “You came back.” Preserve the woman, classroom layout, desks, broken windows, sunlight beams, and muted color palette. The message should look old, dusty, and naturally written in chalk.
xAI Grok Imagine Image Quality Edit edits an input image using natural-language instructions, with support for multiple aspect ratios, two resolution tiers, selectable output formats, and multi-image generation in a single request. It is suitable for image refinement, style changes, composition adjustments, product visuals, and other prompt-driven image editing workflows.
Prompt-based image editing Edit an existing image by describing the changes you want in natural language.
Quality-focused edit workflow Built for higher-quality image editing with support for resolution tiers and multiple output formats.
Flexible aspect ratios
Choose auto to preserve the source framing, or select a preset aspect ratio for a new composition.
Multiple image generation
Generate up to 4 edited variations in one request with num_images.
Multiple output formats
Export results as jpeg, png, or webp.
Simple pricing
Pricing depends only on resolution and num_images.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text prompt describing the desired edit. |
| image | Yes | Input image to edit. Quality edit supports one input image. |
| aspect_ratio | No | Output aspect ratio. Supported values: auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3. Default: auto. |
| resolution | No | Output resolution tier: 1k or 2k. Default: 1k. |
| num_images | No | Number of edited images to generate. Range: 1–4. Default: 1. |
| output_format | No | Output image format: jpeg, png, or webp. Default: jpeg. |
auto to follow the source framing, or pick a preset ratio if you want a different composition.1k for lower cost or 2k for higher-quality output.1 to 4.jpeg, png, or webp.Turn this product photo into a premium studio advertisement with soft cinematic lighting, a clean neutral background, realistic reflections, and polished commercial styling.
Pricing is based on resolution and num_images.
| Resolution | Cost per Image |
|---|---|
| 1k | $0.07 |
| 2k | $0.09 |
| Resolution | 1 Image | 2 Images | 3 Images | 4 Images |
|---|---|---|---|---|
| 1k | $0.07 | $0.14 | $0.21 | $0.28 |
| 2k | $0.09 | $0.18 | $0.27 | $0.36 |
1k costs $0.07 per image2k costs $0.09 per imagenum_imagesaspect_ratio and output_format do not affect pricingnum_images.auto aspect ratio when you want to preserve the original image framing.1k for quick testing and 2k for higher-quality final outputs.num_images when you want multiple edit variations from the same prompt.png when image quality matters more than file size.prompt and image are required.num_images supports values from 1 to 4.aspect_ratio defaults to auto.resolution defaults to 1k.output_format defaults to jpeg.resolution and num_images.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image-quality/edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Grok Imagine Image Quality Edit below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"aspect_ratio": "auto",
"resolution": "1k",
"num_images": 1,
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image-quality/edit" \
-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=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 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' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image-quality/edit";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"aspect_ratio": "auto",
"resolution": "1k",
"num_images": 1,
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}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 = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"aspect_ratio": "auto",
"resolution": "1k",
"num_images": 1,
"output_format": "jpeg"
}
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/x-ai/grok-imagine-image-quality/edit", 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 = task.get("urls", {}).get("get") or 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"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Grok Imagine Image Quality Edit is a xAI model for image editing, exposed as a REST API on WaveSpeedAI. xAI Grok Imagine Image Quality Edit is a fast AI image editing model that edits and enhances images with high-quality visual output using a dedicated RunPod workflow. Ready-to-use REST inference API for photo retouching, creative image edits, product image enhancement, marketing assets, social media visuals, and professional AI image editing workflows with simple integration, no coldstarts, and 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/x-ai/x-ai-grok-imagine-image-quality-edit.
Grok Imagine Image Quality Edit starts at $0.070 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: `prompt`, `image`, `aspect_ratio`, `resolution`, `enable_base64_output`, `num_images`. 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/x-ai/x-ai-grok-imagine-image-quality-edit.
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.
Commercial usage rights depend on the model's license, set by its provider (xAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.