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Home/Models/OpenAI/GPT Image 1 mini
O

GPT Image 1 mini

Invoer:$8/M
Uitvoer:$16/M
Cost-optimized version of GPT Image 1. It is a native Multimodal language model that accepts both text and image input and generates image output.
Nieuw
Commercieel gebruik
Overzicht
Functies
Prijzen
API

Key features

  • Text→Image generation: converts natural-language prompts into images with strong instruction following.
  • Image editing / inpainting: accepts reference images and masks to perform targeted edits.
  • Cost-optimized (“mini”) design: a smaller footprint that OpenAI and observers describe as much cheaper per image than the large model (OpenAI/DevDay messaging and early reports say ~80% less expensive).
  • Flexible output controls: supports size, output format (JPEG/PNG/WEBP), compression and a quality knob (low/medium/high/auto in the cookbook).

Technical details (architecture & capabilities)

  • Model family & input/output: member of the gpt-image-1 family; accepts text prompts and image inputs (for edits) and returns generated image outputs. Quality/size parameters control resolution (typical max ~1536×1024 in this family—see docs for exact supported sizes).
  • Operational tradeoffs: engineered as a smaller footprint model—trades some top-end fidelity for throughput and cost improvements while preserving robust prompt-following and edit features.
  • Safety & metadata: follows OpenAI’s image safety guardrails and embeds C2PA metadata options for provenance when available.

Inputs & outputs — canonical usage supports:

  • Text prompt (string) to generate a new image.
  • Image + mask to perform targeted edits/inpainting.
  • Reference images to control style or composition.
    These are exposed via the Images API (model name gpt-image-1-mini).

Limitations

  • Lower peak fidelity: compared with the large gpt-image-1 model, mini may lose some micro-detail and top-end photorealism (expected tradeoff for cost).
  • Text rendering & tiny details: like many image models, it can struggle with small legible text, dense charts, or micro-fine textures; expect to post-process or use higher-capacity models for those needs.
  • Edit scope: image edit/inpainting features are available but suggest some editing limitations relative to interactive ChatGPT web tools—edits are effective for many tasks but may require iterative refinement.
  • Safety & policy constraints: outputs are subject to OpenAI moderation/safety guardrails (explicit content, copyrighted content restrictions, disallowed outputs). Developers can control moderation sensitivity via API parameters where offered.

Recommended use cases

  • High-volume content generation (marketing assets, thumbnails, rapid concept art) — where cost per image is primary.
  • Programmatic editing / templating — bulk inpainting or variant generation from a base asset.
  • Interactive applications with budget constraints — chat interfaces or integrated design tools where response speed and cost matter more than absolute top fidelity.
  • Prototyping & A/B image generation — generate many candidate images quickly and selectively upscale or re-run on larger models for finalists.
  • How to access gpt-image-1-mini API

Step 1: Sign Up for API Key

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.

img

Step 2: Send Requests to gpt-image-1-mini API

Select the “\**gpt-image-1-mini \**”endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

Functies voor GPT Image 1 mini

<think> 用户要求我将英文文本翻译成荷兰语(Nederlands)。我需要注意： 1. 保持格式和特殊字符（如{} 变量占位符） 2. 技术术语保持准确性 3. 保持语气和风格 4. UI文本要简洁明了 5. 只返回翻译文本，不要添加解释 6. 不要添加任何前缀或说明 原文是： "Explore the key features of GPT Image 1 mini, designed to enhance performance and usability. Discover how these capabilities can benefit your projects and improve user experience." 这看起来是产品或技术介绍的文本，需要翻译成荷兰语。我需要保持GPT Image 1 mini这个占位符不变。 让我翻译： - Explore = Ontdek/Verken - key features = belangrijkste functies/eigenschappen - designed to enhance = ontworpen om te verbeteren - performance = prestaties - usability = bruikbaarheid - Discover = Ontdek - capabilities = mogelijkheden - benefit = ten goede komen/voordeel opleveren - projects = projecten - improve = verbeteren - user experience = gebruikerservaring 翻译： Ontdek de belangrijkste functies van GPT Image 1 mini, ontworpen om prestaties en bruikbaarheid te verbeteren. Ontdek hoe deze mogelijkheden uw projecten ten goede kunnen komen en de gebruikerservaring kunnen verbeteren. 不过"Ontdek"出现了两次，可能需要调整一下： Verken de belangrijkste functies van GPT Image 1 mini, ontworpen om prestaties en bruikbaarheid te verbeteren. Ontdek hoe deze mogelijkheden uw projecten ten goede kunnen komen en de gebruikerservaring kunnen verbeteren. I'll explore how these capabilities can positively impact your projects and optimize the user experience. </think> Verken de belangrijkste functies van GPT Image 1 mini, ontworpen om prestaties en bruikbaarheid te verbeteren. Ontdek hoe deze mogelijkheden uw projecten ten goede kunnen komen en de gebruikerservaring verbeteren.

Prijzen voor GPT Image 1 mini

Ontdek concurrerende prijzen voor GPT Image 1 mini, ontworpen om te passen bij verschillende budgetten en gebruiksbehoeften. Onze flexibele abonnementen zorgen ervoor dat u alleen betaalt voor wat u gebruikt, waardoor het gemakkelijk is om op te schalen naarmate uw vereisten groeien. Ontdek hoe GPT Image 1 mini uw projecten kan verbeteren terwijl de kosten beheersbaar blijven.
Comet Prijs (USD / M Tokens)Officiële Prijs (USD / M Tokens)Korting
Invoer:$8/M
Uitvoer:$16/M
Invoer:$10/M
Uitvoer:$20/M
-20%

Voorbeeldcode en API voor GPT Image 1 mini

gpt-image-1-mini is a cost-optimized, multimodal image model from OpenAI that accepts text and image inputs and produces image outputs. It is positioned as a smaller, cheaper sibling to OpenAI’s full GPT-Image-1 family — designed for high-throughput production use where cost and latency are important constraints. The model is intended for tasks such as text-to-image generation, image editing / inpainting, and workflows that incorporate reference imagery.
Python
JavaScript
Curl
import base64
import os
from openai import OpenAI
from PIL import Image
from io import BytesIO

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
client = OpenAI(api_key=COMETAPI_KEY, base_url="https://api.cometapi.com/v1")

# Output directory
OUTPUT_DIR = os.path.join(os.path.dirname(__file__), "..", "output")
os.makedirs(OUTPUT_DIR, exist_ok=True)

prompt = "A cute baby sea otter swimming in the ocean"

# Generate image using gpt-image-1-mini
result = client.images.generate(
    model="gpt-image-1-mini",
    prompt=prompt,
    size="1024x1024",
)

# Save the image
image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

output_path = os.path.join(OUTPUT_DIR, "output.png")
image = Image.open(BytesIO(image_bytes))
image.save(output_path, format="PNG")

print(f"Image saved to: {output_path}")

Python Code Example

import base64
import os
from openai import OpenAI
from PIL import Image
from io import BytesIO

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
client = OpenAI(api_key=COMETAPI_KEY, base_url="https://api.cometapi.com/v1")

# Output directory
OUTPUT_DIR = os.path.join(os.path.dirname(__file__), "..", "output")
os.makedirs(OUTPUT_DIR, exist_ok=True)

prompt = "A cute baby sea otter swimming in the ocean"

# Generate image using gpt-image-1-mini
result = client.images.generate(
    model="gpt-image-1-mini",
    prompt=prompt,
    size="1024x1024",
)

# Save the image
image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

output_path = os.path.join(OUTPUT_DIR, "output.png")
image = Image.open(BytesIO(image_bytes))
image.save(output_path, format="PNG")

print(f"Image saved to: {output_path}")

JavaScript Code Example

import OpenAI from "openai";
import * as fs from "node:fs";
import * as path from "node:path";
import { fileURLToPath } from "node:url";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/v1";

const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);

const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: BASE_URL,
});

async function main() {
  // Output directory
  const outputDir = path.join(__dirname, "..", "output");
  if (!fs.existsSync(outputDir)) {
    fs.mkdirSync(outputDir, { recursive: true });
  }

  const prompt = "A cute baby sea otter swimming in the ocean";

  // Generate image using gpt-image-1-mini
  const result = await client.images.generate({
    model: "gpt-image-1-mini",
    prompt: prompt,
    size: "1024x1024",
  });

  // Save the image
  const imageBase64 = result.data[0].b64_json;
  const outputPath = path.join(outputDir, "output.png");
  fs.writeFileSync(outputPath, Buffer.from(imageBase64, "base64"));

  console.log(`Image saved to: ${outputPath}`);
}

main();

Curl Code Example

#!/bin/bash
# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here

# Output directory
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
OUTPUT_DIR="$SCRIPT_DIR/../output"
mkdir -p "$OUTPUT_DIR"

curl -s -X POST "https://api.cometapi.com/v1/images/generations" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-1-mini",
    "prompt": "A cute baby sea otter swimming in the ocean",
    "size": "1024x1024"
  }' \
  | jq -r '.data[0].b64_json' | base64 --decode > "$OUTPUT_DIR/output.png"

echo "Image saved to: $OUTPUT_DIR/output.png"

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