Ideogram v2 is an image model with state-of-the-art inpainting, strong prompt comprehension, and accurate in-image text rendering. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Inactivo

$0.08por ejecución·~12 / $1

An illustration of a black running shoe with the text "WaveSpeedAI!" written on theshoe. The shoe is placed on a blue background. The text is white and bold. The overallimage has a modern and techy vibe.

Girl with freckles and curly red hair lying in a field of wildflowers, soft natural light, macro-level skin details, gentle breeze captured in motion

Korean girl in a hanbok standing under cherry blossoms, soft pastel tones, shallow depth of field, cinematic film look, photorealistic

A beautiful typographic poster with the text "Run Ideogram on Replicate", against an epic space scene

Japanese high school boy leaning on a balcony, sunset in the background, uniform details, warm atmosphere, delicate lighting, hyperreal face textures

Woman in a red dress walking through foggy street at night, streetlamp glow behind her, mysterious atmosphere, soft focus background, high fidelity textures

A stunning, realistic portrait of an elderly woman with deep, kind eyes and a gentle smile. She is wearing a hand-knitted, colorful scarf. The photo should be taken in a cozy, sunlit room filled with books. The lighting should be soft and natural, highlighting the texture of her skin and the details of the scarf. a photograph, cinematic, emotional.

A whimsical watercolor illustration for a children's book. A friendly fox wearing a small backpack is reading a book under a large, magical mushroom. The forest around him is vibrant and full of glowing flowers. The words 'WavespeedAI' are subtly integrated into the roots of the mushroom. a painting, vibrant, fantasy.

A sprawling, neon-drenched cyberpunk cityscape at night. Flying vehicles streak between towering skyscrapers covered in holographic advertisements. In the foreground, a lone figure in a long coat stands on a rain-slicked street, looking up at the city. A large, glowing neon sign in Japanese characters reads 'WavespeedAI'. 3d render, cinematic, futuristic, dark.

An architectural visualization of a modern, eco-friendly house integrated into a lush forest. The house features large glass walls, a green roof covered in plants, and natural wood accents. Sunlight streams through the trees, creating dynamic light and shadow on the building's facade. A small sign on the pathway says 'WavespeedAI'. photo, architectural render, realistic, serene.
Ideogram V2 is a powerful text-to-image generation model renowned for its exceptional ability to render text within images. Generate stunning visuals with accurate, readable text — perfect for posters, logos, typography, and designs that require precise text integration.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| image | No | Source image for image-to-image transformation. |
| mask_image | No | Mask for inpainting (white = generate, black = preserve). |
| style | No | Style preset: Auto or specific styles (default: Auto). |
| aspect_ratio | No | Output aspect ratio (default: 1:1). |
| enable_base64_output | No | Return base64 string instead of URL (API only). |
| Aspect Ratio | Best For |
|---|---|
| 1:1 | Instagram posts, social media squares |
| 16:9 | YouTube thumbnails, widescreen displays |
| 9:16 | TikTok, Instagram Stories, mobile content |
| 4:3 | Classic format, presentations |
| 3:4 | Portrait photos, Pinterest |
Text-to-Image:
Image-to-Image:
Inpainting:
| Output | Price |
|---|---|
| Per image | $0.08 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v2 with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ideogram v2 below.
set -euo pipefail
: "${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-v2" \
-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-v2";
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-v2", 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 v2 is a Ideogram model for image generation, exposed as a REST API on WaveSpeedAI. Ideogram v2 is an image model with state-of-the-art inpainting, strong prompt comprehension, and accurate in-image text rendering. 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-v2.
Ideogram v2 starts at $0.080 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`, `enable_base64_output`, `mask_image`, `style`. 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-v2.
Average end-to-end generation time on WaveSpeedAI is around 20 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 (Ideogram). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.