Ideogram V4.5 Image Edit transforms images with written instructions, reference images, masks, and precision controls, supporting targeted edits, visual refinements, composition changes, and professional creative workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.06per run·~16 / $1

Transform the stray cats into regal fantasy cats with subtle magical details: one has a tiny gold crown, one has luminous blue eyes, one has delicate embroidered collar ornaments, and another has faint shimmering fur patterns. Keep them still recognizably cats and preserve the emotional realism of the scene. Elegant magical realism, refined fantasy detail, cinematic night atmosphere.
Ideogram V4.5 Edit modifies an existing image using natural-language instructions, with optional reference images and mask-based control. Use it to change objects, colors, materials, text, layouts, and other visual elements while keeping the source image as the foundation.
Choose between regular editing and high-precision editing depending on how strongly unchanged areas need to be preserved.
Prompt-based image editing
Modify an existing image with natural-language instructions.
Targeted visual changes
Change objects, colors, materials, text, styling, and other image elements.
Reference-image guidance
Add supporting images to guide appearance, products, subjects, or visual direction.
Mask-based editing
Restrict changes to specific regions while preserving the rest of the image.
High-precision mode
Use edit_precision=high when preserving unaffected image regions is especially important.
Four quality tiers
Choose very_low, low, medium, or high depending on cost and output requirements.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Public URL of the source image to edit. |
| prompt | Yes | Text instructions describing the desired edit. Supports 1–10000 characters. |
| reference_images | No | Optional reference image URLs. Supports up to 4 images without a mask, or up to 3 when mask_url is provided. |
| mask_url | No | Mask matching the source image dimensions. Black regions may be edited; white regions are preserved. The mask must contain both editable and preserved areas. |
| aspect_ratio | No | Optional output aspect ratio: 1:1, 4:3, 3:4, 16:9, or 9:16. Leave empty to follow the source image. |
| edit_precision | No | Editing precision: regular or high. Default: regular. |
| quality | No | Generation quality: very_low, low, medium, or high. Default: medium. |
aspect_ratio empty when using edit_precision=high.mask_url, leave aspect_ratio empty.3 reference images.4 reference images.aspect_ratio is omitted, the output follows the source image geometry; large inputs may be downscaled.image is always the source image being edited; reference_images only provide additional guidance.regular for standard editing or high when preservation of unaffected details matters more.very_low, low, medium, or high.Pricing is based only on the selected quality tier.
| Quality | Price per Image |
|---|---|
| Very Low | $0.008 |
| Low | $0.03 |
| Medium | $0.06 |
| High | $0.22 |
The default medium quality edit costs $0.06 per image.
edit_precision, aspect_ratio, mask_url, and the number of reference_images do not add separate charges.
edit_precision=high when unaffected regions need stronger preservation.very_low or low quality for rapid iteration before moving to higher-quality output.image and prompt are required.edit_precision defaults to regular.quality defaults to medium.4 reference images are supported without a mask.3 reference images are supported when a mask is used.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v4.5/edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ideogram v4.5 Edit below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"edit_precision": "regular",
"quality": "medium"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v4.5/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="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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v4.5/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"edit_precision": "regular",
"quality": "medium"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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));
}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 = {
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"edit_precision": "regular",
"quality": "medium"
}
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/ideogram-ai/ideogram-v4.5/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 = 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)Ideogram v4.5 Edit is a Ideogram model for image editing, exposed as a REST API on WaveSpeedAI. Ideogram V4.5 Image Edit transforms images with written instructions, reference images, masks, and precision controls, supporting targeted edits, visual refinements, composition changes, and professional creative workflows. 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 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/ideogram-ai/ideogram-ai-ideogram-v4.5-edit.
Ideogram v4.5 Edit starts at $0.06 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`, `reference_images`, `edit_precision`, `mask_url`. 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/ideogram-ai/ideogram-ai-ideogram-v4.5-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 (Ideogram). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.