Ideogram V3 Turbo produces the highest-quality Ideogram v3 images with photorealistic detail, creative designs, and consistent style. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Bezczynny

$0.03za uruchomienie·~33 / $1

beautiful bauhaus stark typographic poster saying "Ideogram v3 turbo on WaveSpeedAI", pink and yellow

The text "V3 Turbo" in the center middle. A color film-inspired portrait of a young man looking to the side with a shallow depth of field that blurs the surrounding elements, drawing attention to his eye. The fine grain and cast suggest a high ISO film stock, while the wide aperture lens creates a motion blur effect, enhancing the candid and natural documentary style.

Stylized male character with long hair and red cloak standing on a cliff, wind blowing, anime fantasy world background, Ghibli-inspired

A woman in a red silk dress standing beside a rainy window, soft reflections, moody cinematic lighting, ultra-detailed, 85mm photography style

Anime-style schoolgirl under cherry blossoms, soft pastel palette, glowing petals, 2D cel-shaded style, dramatic lighting

Japanese street fashion model in Harajuku, eccentric outfit with vivid colors, layered accessories, candid urban scene, Tokyo vibes

Modern African woman in bold patterned Ankara dress, standing in a desert with a sunset backdrop, fashion editorial style, rich textures

A sprawling futuristic cityscape at dusk, with floating platforms, tall neon-lit skyscrapers, flying cars, moody atmosphere, ultra high detail, cybernetic design, rendered in Unreal Engine style

A futuristic soldier walks through a battlefield full of smoke and debris, camera tracking from behind, slight slow motion, strong contrast lighting, high detail, sci-fi cinematic style

A cute clay-style bunny riding a skateboard through a miniature city, colorful lighting, stop-motion look, playful atmosphere, smooth camera follow, toy-like aesthetic

A magical deer with glowing antlers walks through an enchanted forest, bioluminescent plants lighting the scene, dreamy lighting, fantasy world, fairytale-like animation, slow camera zoom
Generate stunning images with exceptional typography using Ideogram V3 Turbo. This versatile model excels at rendering text within images — perfect for posters, logos, marketing materials, and design work. With support for image editing, mask-based inpainting, and up to 3 reference images, it's a complete creative toolkit.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| image | No | Source image for editing (upload or public URL). |
| mask_image | No | Mask to specify edit regions — white areas will be regenerated. |
| style | No | Output style: Auto, General, Realistic, or Design. Default: Auto. |
| aspect_ratio | No | Output format: 1:1, 16:9, 9:16, 4:3, or 3:4. Default: 1:1. |
| reference_images | No | Up to 3 reference images to guide style and composition. |
| enable_base64_output | No | API only: Returns base64 string instead of URL. |
| Enable Safety Checker | No | Toggle content safety filtering. |
Flat rate per image generation.
| Output | Cost |
|---|---|
| Per image | $0.03 |
| Style | Description | Best For |
|---|---|---|
| Auto | Automatically selects the best style | General use, when unsure |
| General | Balanced, versatile output | Wide range of subjects |
| Realistic | Photorealistic, natural appearance | Photos, portraits, products |
| Design | Graphic design aesthetic | Posters, logos, marketing materials |
| Number of References | Best Use Case |
|---|---|
| 0 | Pure generation from prompt |
| 1 | Match a specific style or composition |
| 2-3 | Combine multiple style elements or ensure consistency |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v3-turbo with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ideogram v3 Turbo below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"style": "Auto",
"aspect_ratio": "1:1"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v3-turbo" \
-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-v3-turbo";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"style": "Auto",
"aspect_ratio": "1:1"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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",
"style": "Auto",
"aspect_ratio": "1:1"
}
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-v3-turbo", 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 v3 Turbo is a Ideogram model for image generation, exposed as a REST API on WaveSpeedAI. Ideogram V3 Turbo produces the highest-quality Ideogram v3 images with photorealistic detail, creative designs, and consistent style. 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-v3-turbo.
Ideogram v3 Turbo starts at $0.030 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`, `enable_base64_output`, `mask_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/ideogram-ai/ideogram-ai-ideogram-v3-turbo.
Median end-to-end generation time on WaveSpeedAI is around 11 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.