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OpenAI's GPT Image 2.5 Flare Text-to-Image generates high-quality images from natural-language prompts, with five quality tiers up to 4K. Flare is the fast, balanced GPT Image 2.5 tier for everyday generation at low latency. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-image
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A stylish young European woman standing in front of a premium retro-futuristic bookstore at night, wearing a sharp black coat and silver boots, holding a red hardcover book in one hand. The storefront is filled with elegant illuminated typography and poster design.

The main sign above the entrance clearly reads:
“THE MIDNIGHT ARCHIVE”

A large window poster clearly reads:
“OPEN UNTIL 2 AM”

A smaller promotional sign beside the door clearly reads:
“RARE BOOKS • ART • DESIGN”

The red book in her hand has the clearly legible title:
“MEMORIES OF TOMORROW”

Sophisticated editorial composition, cinematic blue and amber lighting, realistic glass reflections, clean typography hierarchy, premium graphic design, photorealistic fashion photography, highly detailed, all text perfectly spelled and clearly readable.

$0.024per run·~41 / $1

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ExamplesView all

A stylish young European woman standing in front of a premium retro-futuristic bookstore at night, wearing a sharp black coat and silver boots, holding a red hardcover book in one hand. The storefront is filled with elegant illuminated typography and poster design.

The main sign above the entrance clearly reads:
“THE MIDNIGHT ARCHIVE”

A large window poster clearly reads:
“OPEN UNTIL 2 AM”

A smaller promotional sign beside the door clearly reads:
“RARE BOOKS • ART • DESIGN”

The red book in her hand has the clearly legible title:
“MEMORIES OF TOMORROW”

Sophisticated editorial composition, cinematic blue and amber lighting, realistic glass reflections, clean typography hierarchy, premium graphic design, photorealistic fashion photography, highly detailed, all text perfectly spelled and clearly readable.

A stylish young European woman standing in front of a premium retro-futuristic bookstore at night, wearing a sharp black coat and silver boots, holding a red hardcover book in one hand. The storefront is filled with elegant illuminated typography and poster design. The main sign above the entrance clearly reads: “THE MIDNIGHT ARCHIVE” A large window poster clearly reads: “OPEN UNTIL 2 AM” A smaller promotional sign beside the door clearly reads: “RARE BOOKS • ART • DESIGN” The red book in her hand has the clearly legible title: “MEMORIES OF TOMORROW” Sophisticated editorial composition, cinematic blue and amber lighting, realistic glass reflections, clean typography hierarchy, premium graphic design, photorealistic fashion photography, highly detailed, all text perfectly spelled and clearly readable.

A cinematic product photo of an unbranded amber glass perfume bottle with a plain frosted-glass label and no text or logo, on a marble surface, soft golden-hour lighting, shallow depth of field, elegant reflections, premium editorial photography style

A cinematic product photo of an unbranded amber glass perfume bottle with a plain frosted-glass label and no text or logo, on a marble surface, soft golden-hour lighting, shallow depth of field, elegant reflections, premium editorial photography style

A handsome young Mediterranean man standing on the rooftop of an old apartment building just before a storm, wearing a loose white shirt and dark trousers, struggling to pull a huge white bedsheet from a clothesline as powerful wind turns it into a sail around him, dramatic dark clouds approaching behind the city skyline, warm sunlight breaking through one gap in the clouds, poetic cinematic realism, expressive full-body action.

A handsome young Mediterranean man standing on the rooftop of an old apartment building just before a storm, wearing a loose white shirt and dark trousers, struggling to pull a huge white bedsheet from a clothesline as powerful wind turns it into a sail around him, dramatic dark clouds approaching behind the city skyline, warm sunlight breaking through one gap in the clouds, poetic cinematic realism, expressive full-body action.

Related Models

README

OpenAI GPT Image 2.5 Flare Text-to-Image

OpenAI GPT Image 2.5 Flare Text-to-Image turns natural-language prompts into high-quality images. Flare is the fast, balanced GPT Image 2.5 tier for everyday generation at low latency.

Why Choose This?

  • Strong prompt fidelity Generate images that closely follow detailed natural-language instructions, including scene layout, visual style, and composition.

  • Accurate text rendering Create images with clearer, more usable in-image text for posters, ads, packaging, and interface mockups.

  • Five quality tiers Choose from low drafts to max fidelity and pay only for the detail you need.

  • Up to 4K output and flexible aspect ratios Square, portrait, landscape, and panoramic outputs at 1k, 2k, or 4k.

  • Production-ready API Access the model through a ready-to-use REST inference API for fast integration into applications and workflows.

Parameters

ParameterRequiredDescription
promptYesText description of the desired image.
aspect_ratioNoAspect ratio: 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 2:1, 1:2, 3:1, 1:3, 9:21. Defaults to 1:1.
resolutionNoOutput resolution: 1k (default), 2k, or 4k.
qualityNoQuality tier: low, medium (default), high, xhigh, or max. Higher tiers add detail and cost more.
output_formatNopng (default), jpeg, or webp.

Quality Tiers

GPT Image 2.5 exposes five quality tiers. Pick the lowest tier that meets your need; every step up adds detail, latency, and cost.

TierBest for
lowFast drafts, thumbnails, layout exploration.
mediumThe balanced default for most production images.
highDetailed marketing visuals, text-heavy designs, product shots.
xhighFine textures, intricate scenes, print-ready assets.
maxThe highest-fidelity output the model offers.

How to Use

  1. Write your prompt — describe the image in detail, including subject, style, lighting, composition, and any text you want to appear.
  2. Pick quality and resolution (optional)medium / 1k is the default; raise quality for more detail or resolution for larger output.
  3. Choose aspect ratio (optional)1:1 for square, 2:3 or 9:16 for portrait, 3:2 or 16:9 for landscape, up to 3:1 / 1:3 panoramas.
  4. Submit — run the model and download your generated image.

Example Prompt

A cinematic product photo of a luxury perfume bottle on a marble surface, soft golden-hour lighting, shallow depth of field, elegant reflections, premium editorial photography style

Pricing

Pricing varies by quality and resolution.

Quality1k2k4k
low$0.01$0.02$0.03
medium$0.024$0.04$0.07
high$0.09$0.15$0.27
xhigh$0.16$0.27$0.48
max$0.36$0.60$1.00

Best Use Cases

  • Marketing creatives — Hero images, ad visuals, banners, and campaign assets from text prompts.
  • E-commerce content — Product shots, lifestyle scenes, and promotional visuals without a studio workflow.
  • Landing pages & web design — Branded illustrations, hero sections, and visual mockups.
  • Social media content — Eye-catching visuals tailored to different content formats.
  • Typography-driven visuals — Posters, ads, and packaging concepts that need readable in-image text.

Pro Tips

  • Be specific in your prompt — include subject, environment, camera angle, lighting, mood, and style.
  • For text inside the image, put the exact wording in quotes.
  • Start at medium quality and 1k; move up a tier only if a specific detail is missing.
  • Test multiple aspect ratios when creating assets for different placements.

Notes

  • prompt is the only required field.
  • Requests containing sexual content are rejected before generation and are not charged.

Related Models

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.

Gpt Image 2.5 Flare Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/openai/gpt-image-2.5-flare/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 Gpt Image 2.5 Flare 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",
    "resolution": "1k",
    "quality": "medium",
    "output_format": "png"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/openai/gpt-image-2.5-flare/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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/openai/gpt-image-2.5-flare/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "resolution": "1k",
        "quality": "medium",
        "output_format": "png"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  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",
    "resolution": "1k",
    "quality": "medium",
    "output_format": "png"
}

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/openai/gpt-image-2.5-flare/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 = 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", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Gpt Image 2.5 Flare Text To Image API — Frequently asked questions

What is the Gpt Image 2.5 Flare Text To Image API?

Gpt Image 2.5 Flare Text To Image is a OpenAI model for image generation, exposed as a REST API on WaveSpeedAI. OpenAI's GPT Image 2.5 Flare Text-to-Image generates high-quality images from natural-language prompts, with five quality tiers up to 4K. Flare is the fast, balanced GPT Image 2.5 tier for everyday generation at low latency. 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 Gpt Image 2.5 Flare 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/openai/openai-gpt-image-2.5-flare-text-to-image.

How much does Gpt Image 2.5 Flare Text To Image cost per run?

Gpt Image 2.5 Flare Text To Image starts at $0.024 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 Gpt Image 2.5 Flare Text To Image accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `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/openai/openai-gpt-image-2.5-flare-text-to-image.

How do I get started with the Gpt Image 2.5 Flare Text To Image API?

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.

Can I use Gpt Image 2.5 Flare Text To Image outputs commercially?

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