Ideogram V4 Text-to-Image and Image Edit API generates high-quality images, posters, logos, and marketing visuals from text prompts or reference images. It supports strong typography, sharp detail, flexible output sizes, 1K / 2K resolution tiers, and low / medium / high quality controls. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.05per run·~20 / $1

A young foreign woman in an elegant one-piece swimsuit standing on a quiet beach at sunset, soft golden light, gentle ocean waves, wind moving her hair and a light sheer cover-up, poised and natural posture, cinematic fashion editorial photography, refined composition, luxurious summer atmosphere, tasteful and artistic, high-end magazine style, realistic skin texture, soft shadows

A bold urban mural, "YOU ARE HERE" in oversized 3D block letters, glowing sunset gradient with turquoise accents, surrounded by blooming flowers, doves, and leafy branches flowing outward from the text, photorealistic exterior wall, mural paint texture, positive reflective message, energetic public art style
Ideogram V4 generates high-quality images, posters, and logos from natural-language prompts with strong typography, sharp detail, and flexible output sizes. It supports both text-to-image and image-to-image workflows, with selectable resolution, aspect ratio, quality, and output format.
1k / 2k and low / medium / high to balance speed, detail, and cost.jpeg, png, or webp.| Parameter | Required | Default | Description |
|---|---|---|---|
prompt | Yes | — | Text description of the image to generate or edit. |
image | No | — | Optional input image for image-to-image editing. When provided, the model edits this image guided by the prompt. |
strength | No | 0.65 | Image-to-image edit strength. Lower values keep the result closer to the source image; higher values allow stronger changes. |
resolution | No | 1k | Output resolution tier: 1k or 2k. |
aspect_ratio | No | 1:1 | Output aspect ratio: 1:1, 3:2, 2:3, 4:3, 3:4, 16:9, 9:16, 21:9, 9:21. |
quality | No | medium | Quality tier: low, medium, or high. |
output_format | No | jpeg | Output image format: jpeg, png, or webp. |
image when you want to edit or restyle an existing image.strength to control how strongly the source image should be changed.resolution, aspect_ratio, quality, and output_format.A bold urban mural, "YOU ARE HERE" in oversized 3D block letters, glowing sunset gradient with turquoise accents, surrounded by blooming flowers, doves, and leafy branches flowing outward from the text, photorealistic exterior wall, mural paint texture, positive reflective message, energetic public art style
Price depends on selected resolution and quality.
| Resolution | low | medium | high |
|---|---|---|---|
| 1k | $0.025 | $0.05 | $0.10 |
| 2k | $0.05 | $0.10 | $0.20 |
1:1 for square social graphics, 3:4 or 4:3 for posters, and 16:9 or 9:16 for widescreen or vertical layouts.2k + high for final assets where detail matters.1k + low for fast drafts.strength 0.5 to 0.65 for a guided edit, and raise it for stronger reinterpretation.prompt is required.image, strength, resolution, aspect_ratio, quality, and output_format are optional.strength is 0.65.resolution is 1k.aspect_ratio is 1:1.quality is medium.output_format is jpeg.resolution and quality.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v4 with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ideogram v4 below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"strength": 0.65,
"resolution": "1k",
"aspect_ratio": "1:1",
"quality": "medium",
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v4" \
-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/ideogram-ai/ideogram-v4";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"strength": 0.65,
"resolution": "1k",
"aspect_ratio": "1:1",
"quality": "medium",
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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",
"strength": 0.65,
"resolution": "1k",
"aspect_ratio": "1:1",
"quality": "medium",
"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/ideogram-ai/ideogram-v4", 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)Ideogram v4 is a Ideogram model for image editing, exposed as a REST API on WaveSpeedAI. Ideogram V4 Text-to-Image and Image Edit API generates high-quality images, posters, logos, and marketing visuals from text prompts or reference images. It supports strong typography, sharp detail, flexible output sizes, 1K / 2K resolution tiers, and low / medium / high quality controls. 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 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/ideogram-ai/ideogram-ai-ideogram-v4.
Ideogram v4 starts at $0.050 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`, `output_format`, `quality`. 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.
Median end-to-end generation time on WaveSpeedAI is around 37 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Ideogram). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.