openai/gpt-image-2.5-flare/text-to-image

نص إلى صورة

GPT Image 2.5 Flare Text-to-Image API by OpenAI

openai/gpt-image-2.5-flare/text-to-image

Text-to-image

GPT Image 2.5 Flare generates images from natural-language prompts with arbitrary resolutions up to 3840x2160, five quality tiers including xhigh and max, and first-class transparent backgrounds. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

مقارنة النماذج

GPT Image 2.5 Flare Text-to-Image من تطوير OpenAI. توفّر Atlas Cloud (التي تُشغّلها Atlas Cloud AI LLC) إمكانية الوصول إليه ولا تملكه. جميع العلامات التجارية ملك لأصحابها المعنيين.

الإدخال

الطلب *

الجودة

الحجم

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Background

صيغة الإخراج

العدد

الإخراج

في انتظار التنفيذ

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قم بتعيين المعاملات وانقر فوق تشغيل لبدء الإنشاء

كل مرة ستكلف ≈$0.003 مع $10 يمكنك التشغيل حوالي 3333 مرةيتم احتساب تكلفة هذا النموذج بالرموز (tokens): يُقاس النص والصور المرجعية المُدخلة والصورة المُولَّدة جميعها بالرموز. المبلغ أعلاه تقدير وفق إعداداتك الحالية — الأحجام الأكبر ومستويات الجودة الأعلى والمزيد من الصور المرجعية تستهلك رموزًا أكثر وتكلّف أكثر.

يمكنك المتابعة بـ:

صورة إلى فيديو صورة إلى صورة

المعلمات

مثال الكود
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "openai/gpt-image-2.5-flare/text-to-image",  # Required. Model name. options: openai/gpt-image-2.5-flare/text-to-image
    "prompt": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot.",  # Required. Text description of the desired image
    "quality": "medium",  # Rendering quality tier. options: auto | low | medium | high | xhigh | max
    "size": "1024x1024",  # optional string or auto or 1024x1024 or 1536x1024 or 5 moreThe size ofthe generated images
    "background": "auto",  # Background of the generated image. options: auto | opaque | transparent
    "output_format": "png",  # Output image format. options: png | jpeg | webp
    "moderation": "auto",  # Content-moderation strictness. options: auto | low
    "n": 1,  # Number of images to generate, 1 to 10. (min: 1, max: 10)
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

التثبيت

قم بتثبيت الحزمة المطلوبة للغة البرمجة الخاصة بك.

pip install requests

المصادقة

تتطلب جميع طلبات API المصادقة عبر مفتاح API. يمكنك الحصول على مفتاح API الخاص بك من لوحة تحكم Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

ترويسات HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

حافظ على أمان مفتاح API الخاص بك

لا تكشف أبدًا مفتاح API الخاص بك في الكود من جانب العميل أو المستودعات العامة. استخدم متغيرات البيئة أو وكيل الخادم الخلفي بدلاً من ذلك.

إرسال طلب

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

إرسال طلب

أرسل طلب توليد غير متزامن. تُرجع API معرّف التنبؤ الذي يمكنك استخدامه للتحقق من الحالة واسترداد النتيجة.

POST/api/v1/model/generateImage

نص الطلب

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "openai/gpt-image-2.5-flare/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

الاستجابة

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

التحقق من الحالة

استعلم عن نقطة نهاية التنبؤ للتحقق من الحالة الحالية لطلبك.

GET/api/v1/model/prediction/{prediction_id}

مثال الاستعلام

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

قيم الحالة

processingلا يزال الطلب قيد المعالجة.

completedاكتمل التوليد. المخرجات متاحة.

succeededنجح التوليد. المخرجات متاحة.

failedفشل التوليد. تحقق من حقل الخطأ.

استجابة مكتملة

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

رفع الملفات

ارفع الملفات إلى تخزين Atlas Cloud واحصل على URL يمكنك استخدامه في طلبات API الخاصة بك. استخدم multipart/form-data للرفع.

POST/api/v1/model/uploadMedia

مثال الرفع

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

الاستجابة

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

المعاملات التالية مقبولة في نص الطلب.

الإجمالي: 8مطلوب: 2اختياري: 6

modelstringrequired

Model name.

Default: "openai/gpt-image-2.5-flare/text-to-image"

openai/gpt-image-2.5-flare/text-to-image

promptstringrequired

Text description of the desired image. Up to 32000 characters.

Default: "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot."

qualitystring

Rendering quality tier. gpt-image-2.5 adds xhigh and max on top of low/medium/high. Higher tiers cost more per image.

Default: "medium"

autolowmediumhighxhighmax

sizestring

optional string or auto or 1024x1024 or 1536x1024 or 5 moreThe size ofthe generated images.For gpt-image-2.5 is supported as WIDTHxHEIGHT strings,for example 1536x864 . Width and height mustboth be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1.Resolutions above2560x1440 are experimental, and the maximum supported resolution is 3840x2160 .The requesteosize must also satisfy the model's current pixel and edge limits.The standard sizes 1024x1024.1536x1024 ,and 1024x1536 are supported by the GPT image models; auto is supported for modelsthat allow automatic sizing.For dall-e-2,use oneof 256x256,512x512,or 1024x1024.Fordall-e-3,use oneof 1024x1024,1792x1024,or 1024x1792.

Default: "1024x1024"

auto1024x10241024x768768x10241024x12801024x15361536x10242048x20482048x11521152x20482560x10881088x25602880x21602160x28803840x21602160x3840

backgroundstring

Background of the generated image. When using transparent, set the output format to png or webp.

Default: "auto"

autoopaquetransparent

output_formatstring

Output image format.

Default: "png"

pngjpegwebp

moderationstring

Content-moderation strictness. low applies less restrictive filtering.

Default: "auto"

autolow

ninteger

Number of images to generate, 1 to 10. Each image is billed separately.

Default: 1Min: 1Max: 10

مثال على نص الطلب

{
  "model": "openai/gpt-image-2.5-flare/text-to-image",
  "prompt": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot.",
  "quality": "medium",
  "size": "1024x1024",
  "background": "auto",
  "output_format": "png",
  "moderation": "auto",
  "n": 1
}

Output Schema

تُرجع API استجابة تنبؤ تحتوي على عناوين URL للمخرجات المولّدة.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

statusstring

Status of the task: created, processing, completed, or failed.

outputsarray

Array of URLs to the generated images. Empty when status is not completed.

created_atstring

ISO timestamp of when the request was created.

مثال على الاستجابة

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

يدمج Atlas Cloud Skills أكثر من 400 نموذج ذكاء اصطناعي مباشرة في مساعد البرمجة بالذكاء الاصطناعي الخاص بك. أمر واحد للتثبيت، ثم استخدم اللغة الطبيعية لتوليد الصور ومقاطع الفيديو والدردشة مع LLM.

العملاء المدعومون

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ العملاء المدعومون

التثبيت

npx skills add AtlasCloudAI/atlas-cloud-skills

إعداد مفتاح API

احصل على مفتاح API الخاص بك من لوحة تحكم Atlas Cloud وعيّنه كمتغير بيئة.

export ATLASCLOUD_API_KEY="your-api-key-here"

الإمكانيات

بمجرد التثبيت، يمكنك استخدام اللغة الطبيعية في مساعد الذكاء الاصطناعي الخاص بك للوصول إلى جميع نماذج Atlas Cloud.

توليد الصورأنشئ صورًا باستخدام نماذج مثل Nano Banana 2 و Z-Image والمزيد.

إنشاء الفيديوأنشئ مقاطع فيديو من نص أو صور باستخدام Kling و Vidu و Veo وغيرها.

دردشة LLMتحدث مع Qwen و DeepSeek ونماذج اللغة الكبيرة الأخرى.

رفع الوسائطارفع الملفات المحلية لتحرير الصور وسير عمل تحويل الصور إلى فيديو.

MCP Server

يربط Atlas Cloud MCP Server بيئة التطوير الخاصة بك بأكثر من 400 نموذج ذكاء اصطناعي عبر Model Context Protocol. يعمل مع أي عميل متوافق مع MCP.

العملاء المدعومون

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ العملاء المدعومون

التثبيت

npx -y atlascloud-mcp

التكوين

أضف التكوين التالي إلى ملف إعدادات MCP في بيئة التطوير الخاصة بك.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

الأدوات المتاحة

atlas_generate_imageتوليد صور من أوصاف نصية.

atlas_generate_videoإنشاء مقاطع فيديو من نص أو صور.

atlas_chatالدردشة مع نماذج اللغة الكبيرة.

atlas_list_modelsتصفح أكثر من 400 نموذج ذكاء اصطناعي متاح.

atlas_quick_generateإنشاء محتوى بخطوة واحدة مع اختيار تلقائي للنموذج.

atlas_upload_mediaرفع الملفات المحلية لسير عمل API.

اعرف المزيد

github.com/AtlasCloudAI/mcp-server

مخطط API

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "GPT Image 2.5 Flare text-to-image (OpenAI Images API)."
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "required": [
          "model",
          "prompt"
        ],
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "openai/gpt-image-2.5-flare/text-to-image",
            "enum": [
              "openai/gpt-image-2.5-flare/text-to-image"
            ]
          },
          "prompt": {
            "type": "string",
            "maxLength": 32000,
            "default": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot.",
            "description": "Text description of the desired image. Up to 32000 characters."
          },
          "quality": {
            "type": "string",
            "default": "medium",
            "enum": [
              "auto",
              "low",
              "medium",
              "high",
              "xhigh",
              "max"
            ],
            "description": "Rendering quality tier. gpt-image-2.5 adds xhigh and max on top of low/medium/high. Higher tiers cost more per image.",
            "x-ui-component": "select"
          },
          "size": {
            "default": "1024x1024",
            "description": "optional string or auto or 1024x1024 or 1536x1024 or 5 moreThe size ofthe generated images.For gpt-image-2.5 is supported as WIDTHxHEIGHT strings,for example 1536x864 . Width and height mustboth be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1.Resolutions above2560x1440 are experimental, and the maximum supported resolution is 3840x2160 .The requesteosize must also satisfy the model's current pixel and edge limits.The standard sizes 1024x1024.1536x1024 ,and 1024x1536 are supported by the GPT image models; auto is supported for modelsthat allow automatic sizing.For dall-e-2,use oneof 256x256,512x512,or 1024x1024.Fordall-e-3,use oneof 1024x1024,1792x1024,or 1024x1792.",
            "enum": [
              "auto",
              "1024x1024",
              "1024x768",
              "768x1024",
              "1024x1280",
              "1024x1536",
              "1536x1024",
              "2048x2048",
              "2048x1152",
              "1152x2048",
              "2560x1088",
              "1088x2560",
              "2880x2160",
              "2160x2880",
              "3840x2160",
              "2160x3840"
            ],
            "type": "string"
          },
          "background": {
            "type": "string",
            "default": "auto",
            "enum": [
              "auto",
              "opaque",
              "transparent"
            ],
            "description": "Background of the generated image. When using transparent, set the output format to png or webp.",
            "x-ui-component": "select"
          },
          "output_format": {
            "type": "string",
            "default": "png",
            "enum": [
              "png",
              "jpeg",
              "webp"
            ],
            "description": "Output image format.",
            "x-ui-component": "select"
          },
          "moderation": {
            "type": "string",
            "default": "auto",
            "enum": [
              "auto",
              "low"
            ],
            "description": "Content-moderation strictness. low applies less restrictive filtering.",
            "x-ui-component": "select"
          },
          "n": {
            "type": "integer",
            "minimum": 1,
            "maximum": 10,
            "default": 1,
            "description": "Number of images to generate, 1 to 10. Each image is billed separately."
          }
        },
        "x-order-properties": [
          "model",
          "prompt",
          "quality",
          "size",
          "background",
          "output_format",
          "n"
        ],
        "allOf": [
          {
            "if": {
              "properties": {
                "background": {
                  "const": "transparent"
                }
              },
              "required": [
                "background"
              ]
            },
            "then": {
              "properties": {
                "output_format": {
                  "enum": [
                    "png",
                    "webp"
                  ]
                }
              }
            }
          }
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique identifier for the prediction."
          },
          "urls": {
            "type": "object",
            "description": "Object containing related API endpoints."
          },
          "model": {
            "type": "string",
            "description": "Model ID used for the prediction."
          },
          "status": {
            "type": "string",
            "description": "Status of the task: created, processing, completed, or failed."
          },
          "outputs": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "Array of URLs to the generated images. Empty when status is not completed."
          },
          "created_at": {
            "type": "string",
            "format": "date-time",
            "description": "ISO timestamp of when the request was created."
          }
        }
      }
    }
  }
}

قالب موجه LLM

# openai/gpt-image-2.5-flare/text-to-image

> GPT Image 2.5 Flare generates images from natural-language prompts with arbitrary resolutions up to 3840x2160, five quality tiers including xhigh and max, and first-class transparent backgrounds. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `openai/gpt-image-2.5-flare/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"openai/gpt-image-2.5-flare/text-to-image"`
  - Options: "openai/gpt-image-2.5-flare/text-to-image"

- **`prompt`** (`string`, _required_):
  Text description of the desired image. Up to 32000 characters.
  - Default: `"A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot."`

- **`quality`** (`string`, _optional_):
  Rendering quality tier. gpt-image-2.5 adds xhigh and max on top of low/medium/high. Higher tiers cost more per image.
  - Default: `"medium"`
  - Options: "auto", "low", "medium", "high", "xhigh", "max"

- **`size`** (`string`, _optional_):
  optional string or auto or 1024x1024 or 1536x1024 or 5 moreThe size ofthe generated images.For gpt-image-2.5 is supported as WIDTHxHEIGHT strings,for example 1536x864 . Width and height mustboth be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1.Resolutions above2560x1440 are experimental, and the maximum supported resolution is 3840x2160 .The requesteosize must also satisfy the model's current pixel and edge limits.The standard sizes 1024x1024.1536x1024 ,and 1024x1536 are supported by the GPT image models; auto is supported for modelsthat allow automatic sizing.For dall-e-2,use oneof 256x256,512x512,or 1024x1024.Fordall-e-3,use oneof 1024x1024,1792x1024,or 1024x1792.
  - Default: `"1024x1024"`
  - Options: "auto", "1024x1024", "1024x768", "768x1024", "1024x1280", "1024x1536", "1536x1024", "2048x2048", "2048x1152", "1152x2048", "2560x1088", "1088x2560", "2880x2160", "2160x2880", "3840x2160", "2160x3840"

- **`background`** (`string`, _optional_):
  Background of the generated image. When using transparent, set the output format to png or webp.
  - Default: `"auto"`
  - Options: "auto", "opaque", "transparent"

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"png"`
  - Options: "png", "jpeg", "webp"

- **`n`** (`integer`, _optional_):
  Number of images to generate, 1 to 10. Each image is billed separately.
  - Default: `1`
  - Min: 1
  - Max: 10



**Required Parameters Example**:

```json
{
  "model": "openai/gpt-image-2.5-flare/text-to-image",
  "prompt": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot."
}
```


**Full Example**:

```json
{
  "model": "openai/gpt-image-2.5-flare/text-to-image",
  "prompt": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot.",
  "quality": "medium",
  "size": "1024x1024",
  "background": "auto",
  "output_format": "png",
  "n": 1
}
```


### Output Schema

The API returns the following output format:


- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated images. Empty when status is not completed.

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.



**Example Response**:

```json
{
  "id": "",
  "urls": {},
  "model": "",
  "status": "",
  "outputs": [
    ""
  ],
  "created_at": ""
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "openai/gpt-image-2.5-flare/text-to-image",
  "prompt": "A neon-lit ramen stall on a rainy Tokyo street, cinematic wide shot.",
  "quality": "medium",
  "size": "1024x1024",
  "background": "auto",
  "output_format": "png",
  "n": 1
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/openai/gpt-image-2.5-flare/text-to-image)

A sleek futuristic aircraft hovering silently above an endless desert, enormous dunes flowing like waves beneath it, several tiny figures walking across the sand below, distant storm clouds approaching across the horizon, sunlight breaking through the clouds, long shadows stretching across the dunes, minimal futuristic design, mysterious and elegant, cinematic science fiction, immense scale, atmospheric perspective, subtle film grain, realistic materials, dramatic composition, photorealistic, 8K

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