Seedance 2.5 Now Live | Try in Video Generator →
Home/Explore/Reve/2.1/Text To Image

reve/

Reve 2.1 Text-to-Image generates high-quality images from text prompts, with strong layout intelligence, accurate text rendering, and reliable composition for posters, ads, product visuals, and typography-rich designs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-image
Input

Idle

A young foreign woman standing beside a suitcase in an airport terminal at night, holding a boarding pass, looking through a large glass wall at a departing airplane, reflections of city lights and passengers around her, emotional farewell story, modern cinematic composition, soft blue lighting, realistic photography

$0.28per run·~35 / $10

Next:

ExamplesView all

A young foreign woman standing beside a suitcase in an airport terminal at night, holding a boarding pass, looking through a large glass wall at a departing airplane, reflections of city lights and passengers around her, emotional farewell story, modern cinematic composition, soft blue lighting, realistic photography

A young foreign woman standing beside a suitcase in an airport terminal at night, holding a boarding pass, looking through a large glass wall at a departing airplane, reflections of city lights and passengers around her, emotional farewell story, modern cinematic composition, soft blue lighting, realistic photography

Related Models

README

Reve 2.1 Text to Image

Reve 2.1 Text to Image generates detailed, layout-aware images from natural-language prompts. It is built for dense compositions, accurate text rendering, and high-resolution visual creation across editorial, marketing, product, and creative workflows.

Why Choose This?

  • Detailed image generation
    Create high-quality images from natural-language prompts.

  • Layout-aware composition
    Generate structured visuals with clear subject placement, visual hierarchy, and scene organization.

  • Strong text rendering
    Suitable for prompts that require readable text, posters, labels, or graphic layouts.

  • Standard image output
    Generated images are returned as URLs in the standard WaveSpeed prediction response.

Parameters

ParameterRequiredDescription
promptYesText description of the image to generate.
aspect_ratioNoOutput aspect ratio, including 1:1, 16:9, 9:16, 4:3, 3:4, and other supported presets.
output_formatNoOutput format: png, jpeg, or webp.

How to Use

  1. Write your prompt — Describe the subject, composition, style, lighting, and any text that should appear in the image.
  2. Choose aspect ratio — Select an aspect ratio to let the model choose the best layout.
  3. Choose output format — Select png, jpeg, or webp when needed.
  4. Submit — Generate the image and retrieve the output URL.

Pricing

OutputPrice
One image$0.28

Best Use Cases

  • Editorial visuals — Generate structured visuals for articles, covers, and layout-driven creative assets.
  • Marketing images — Create campaign visuals, promotional graphics, and branded content.
  • Product concepts — Explore product scenes, packaging ideas, and commercial compositions.
  • Text-heavy designs — Generate posters, signs, labels, and dense layouts with readable text.
  • Creative image generation — Produce high-resolution visual concepts from detailed prompts.

Pro Tips

  • Describe layout, hierarchy, and the relationship between major elements.
  • Put exact wording in quotation marks when text must appear in the image.
  • Be specific about subject placement, lighting, color palette, and visual style.
  • Use png for high-quality general output, jpeg for smaller files, and webp for web-friendly images.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

2.1 Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/reve/2.1/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 2.1 Text To Image below.

HTTP example
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",
    "aspect_ratio": "1:1",
    "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/reve/2.1/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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/reve/2.1/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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));
}
Python example
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",
    "aspect_ratio": "1:1",
    "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/reve/2.1/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)

2.1 Text To Image API — Frequently asked questions

What is the 2.1 Text To Image API?

2.1 Text To Image is a Reve model for image generation, exposed as a REST API on WaveSpeedAI. Reve 2.1 Text-to-Image generates high-quality images from text prompts, with strong layout intelligence, accurate text rendering, and reliable composition for posters, ads, product visuals, and typography-rich designs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the 2.1 Text To Image API?

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/reve/reve-2.1-text-to-image.

How much does 2.1 Text To Image cost per run?

2.1 Text To Image starts at $0.28 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.

What inputs does 2.1 Text To Image accept?

Key inputs: `prompt`, `aspect_ratio`, `enable_base64_output`, `enable_sync_mode`, `output_format`. 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/reve/reve-2.1-text-to-image.

How long does 2.1 Text To Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 42 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use 2.1 Text To Image outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Reve). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Reve 2.1 Text to Image API on WaveSpeedAI