Krea 2 Large Text to Image is a fast AI image generation model that creates high-fidelity images from text prompts with aspect ratio, creativity, and optional style reference controls. Ready-to-use REST inference API for creative design, marketing visuals, product mockups, brand assets, social media content, concept art, and professional text-to-image workflows with simple integration, no coldstarts, and affordable pricing.
Idle

$0.06per run·~16 / $1

A dramatic luxury beauty portrait of an adult female model in a dark elegant background, soft golden rim light, glossy skin highlights, refined makeup, cinematic shadows, high-end skincare campaign style, photorealistic, ultra-detailed
WaveSpeed AI Krea V2 Large Text-to-Image generates high-quality images from natural-language prompts, with optional reference images for stronger style guidance. It is designed for premium prompt-based image generation workflows where you want flexible aspect ratios, controllable creativity, and the option to steer the final look with one or more visual references.
High-quality text-to-image generation
Create polished images from detailed natural-language prompts.
Reference-guided style control
Add up to 10 reference images to guide the visual style of the generated result.
Flexible aspect ratios
Choose from multiple preset aspect ratios for square, portrait, landscape, or cinematic compositions.
Creativity control
Adjust how loosely the model interprets the prompt with raw, low, medium, or high.
Multi-reference support
Use multiple references with individual strength values for more nuanced style influence.
Production-ready workflow
Suitable for concept art, marketing visuals, brand creatives, editorial imagery, and visual ideation.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image to generate. Supports 1–5000 characters. |
| size | No | Output aspect ratio. Supported values: 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 2:3, 9:16. Default: 1:1. |
| creativity | No | Controls how loosely the model interprets the prompt. Supported values: raw, low, medium, high. Default: medium. |
| reference | No | Optional reference images that guide the style of the generated image. Supports up to 10 items. |
Each item in the reference array supports:
| Field | Required | Description |
|---|---|---|
| image_url | Yes | Reference image URL. |
| strength | No | How strongly the reference image influences the generated image. Range: -2 to 2. Default: 1. |
raw or low for tighter prompt control, or medium / high for looser interpretation.A premium editorial portrait of a woman in soft window light, natural skin texture, elegant neutral wardrobe, cinematic depth of field, refined luxury-magazine styling
Pricing is based on whether you use reference images.
| Mode | Cost |
|---|---|
| Without reference images | $0.06 |
| With one or more reference images | $0.065 |
reference images adds $0.005 to the requestaspect_ratio and creativity do not affect pricingraw or low creativity when you want stricter prompt fidelity.medium or high when you want more interpretive or stylized output.strength carefully when combining several references, especially if their styles differ.prompt is required.reference is optional and supports up to 10 images.strength value from -2 to 2.creativity defaults to medium.aspect_ratio defaults to 1:1.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/krea-v2-large/text-to-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Krea v2 Large Text To Image below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1:1",
"creativity": "medium"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/krea-v2-large/text-to-image" \
-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/wavespeed-ai/krea-v2-large/text-to-image";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1:1",
"creativity": "medium"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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",
"size": "1:1",
"creativity": "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/wavespeed-ai/krea-v2-large/text-to-image", 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)Krea v2 Large Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. Krea 2 Large Text to Image is a fast AI image generation model that creates high-fidelity images from text prompts with aspect ratio, creativity, and optional style reference controls. Ready-to-use REST inference API for creative design, marketing visuals, product mockups, brand assets, social media content, concept art, and professional text-to-image 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/wavespeed-ai/krea-v2-large-text-to-image.
Krea v2 Large Text To Image starts at $0.060 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`, `size`, `creativity`, `reference`. 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/wavespeed-ai/krea-v2-large-text-to-image.
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 (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.