How fast is GPT Image 1.5 compared to GPT Image 1?

GPT Image 1.5 delivers up to 4× speed improvements over GPT Image 1, significantly reducing latency for iterative creative workflows.

Does GPT Image 1.5 support transparent backgrounds?

Yes, set the background parameter to 'transparent' with PNG or WebP output formats. Transparency works best at medium or high quality settings.

What is the maximum text prompt length for GPT Image 1.5?

GPT Image 1.5 accepts prompts up to 32,000 characters, enabling highly detailed and constrained instructions for complex image generation tasks.

How does GPT Image 1.5 compare to Google's Nano Banana Pro?

GPT Image 1.5 emphasizes editing fidelity and iteration speed, while Nano Banana Pro is praised for studio realism. Both are closely competitive—choose based on your workflow needs.

Does GPT Image 1.5 support multi-turn conversational editing?

Yes, through the Responses API, GPT Image 1.5 supports multi-turn editing workflows where you can iteratively refine images by providing follow-up instructions while preserving context.

Can GPT Image 1.5 use multiple reference images for compositing?

Yes, GPT Image 1.5 accepts multiple input images for compositing and style reference. The first 5 images are preserved with higher fidelity when using high input_fidelity mode.

What resolutions and quality settings does GPT Image 1.5 support?

GPT Image 1.5 supports 1024×1024 (square), 1536×1024 (landscape), and 1024×1536 (portrait). Quality options include low, medium, high, and auto.

OpenAI

Available

gpt-image-1.5

GPT Image 1.5 API

GPT-Image-1.5 is OpenAI’s image model in the GPT Image family . It is a natively multimodal GPT model designed to generate images from text prompts and to perform high-fidelity edits of input images while following user instructions closely.

Starting price

$4.00 / 1M input tokens

Usage-based billing

API health

Available

Production endpoint

Response

Async ready

Observed API response

Released

Dec 17, 2025

OpenAI

Playground

Try GPT Image 1.5 with a real request, review its parameters and validate the output before integrating the API.

Pricing

Use the quick estimate above for a single run, then review the full CometAPI and official-price comparison.

First request

$0.0120

Estimated CometAPI usage cost

Ten requests

$0.1200

Estimated CometAPI usage cost

Fifteen requests

$0.1800

Estimated CometAPI usage cost

⇌

Credits conversion

1,000 credits = $1

Credits make budgets comparable across token, request and runtime billing. The USD amount remains the source of truth at checkout.

✓Current model in credits

Input

4,000

credits / 1M tokens

Output

8,000

credits / 1M tokens

Minimum charge transparency This prototype does not assume a hidden per-request minimum. If a production billing floor or minimum top-up applies, it must be displayed before purchase and included in every budget estimate.

Model	Comet Price (USD / M Tokens)	Official Price (USD / M Tokens)	Discount
gpt-image-1.5	Input: $4.00/M Output: $8.00/M	Input: $5.00/M Output: $10.00/M	-20%
gpt-image-1.5-2025-12-16	Input: $4.00/M Output: $8.00/M	Input: $5.00/M Output: $10.00/M	-20%

Model brief

A stable model identity for search and evaluation, paired with live catalog data that can change without rewriting the page's core SEO structure.

Stable identity

What is GPT Image 1.5?

Canonical model identity stays stable as pricing and limits change.

Live model data

Current catalog snapshot

Availability

Available

Starting price

$4.00 / 1M input tokens

Context

See capabilities

Catalog date

Dec 17, 2025

Overview

A practical overview of GPT Image 1.5, including important behavior and integration considerations.

What is the GPT-Image-1.5 API?

GPT-Image-1.5 is the newest member of OpenAI’s GPT Image family and the model behind ChatGPT’s revamped Images experience. It’s designed to move image generation from novelty experiments into production-grade creative tooling: higher photorealism, finer control for iterative edits, and faster inference to support interactive and enterprise workflows.

The gpt-image-1.5 API is a multimodal image model endpoint that accepts one or more image inputs (file identifiers or bytes) plus a text prompt and returns generated images or edited images. It supports:

Text-to-image generation (create from prompt),
Image editing / in-painting / compositing (apply instructions to existing images, multiple image inputs allowed), and
Iterative, multi-turn editing workflows through the Responses API (enables “tweak & iterate” UIs).

The API treats image prompts differently from old DALL·E limits: GPT image models accept significantly longer text prompts (the 32k-character guideline), making complex, constraint-heavy instructions feasible.

Main features (practical)

Improved editability / multi-turn consistency: preserves character appearance, lighting and key visual attributes across iterative edits. This makes “same model, repeated edits” more reliable for workflows like product catalogs or brand assets.
Faster throughput — 4× speed improvements over GPT Image 1, aimed at lowering latency for iterative creative workflows.
Cost optimizations — image input/output costs reduced by about 20% vs. GPT Image 1, lowering per-image iteration costs for high-volume users.
Multi-image compositing & style referencing — accept multiple reference images to composite scenes or transfer style/lighting.
Quality/fidelity knobs — API parameters that trade off speed vs. fidelity (use lower quality for bulk generation; higher quality for production assets).
Multi-turn editing / Responses API integration — enables stepwise workflows (ask for changes, then “make tweaks” preserving state).

Technical capabilities

Text prompt limit (image models): up to 32,000 characters (note: OpenAI documents this as the text length allowance for GPT image models). Use this for long, constraint-heavy prompts.
Image inputs: accepts File IDs (preferred for multi-turn flows) or raw bytes; multiple images may be provided for compositing and reference.
Outputs: PNG/JPEG or platform default image artifacts returned by the API (or as attachments within ChatGPT). Outputs can include multiple candidate images and support iterative requests to refine an output.
Generation modes: text-to-image, image editing (inpaint/extend with instructions), and variants. Multi-turn editing supports “add/subtract/combine” style instructions.
Instruction-aware editing: models are optimized for instruction fidelity (preserving specified invariants like “do not change the logo”, “keep pose and lighting”). Prompt-engineering patterns (explicit invariants repeated each iteration) reduce semantic drift.

Benchmark performance

Leaderboard placement: One aggregate report cited GPT Image 1.5 leading text-to-image rankings with ~1264 points on an Artificial Analysis leaderboard, ahead of the next model by a measurable margin.
Task-level metrics (edit & preservation): a Microsoft Foundry summary of evaluation metrics shows GPT-Image-1.5 achieving near-perfect binary modification success (100% on a single-turn BinaryEval) and strong face-preservation scores (around 90% on AuraFace measures) in their comparison table versus competitors and previous OpenAI models. Those comparative metrics place GPT-Image-1.5 ahead of some rivals on preservation and edit fidelity.

GPT Image 1.5

How GPT-Image-1.5 compares to peers

Vs. GPT Image 1 (previous OpenAI generation): faster (up to 4×), cheaper (~20% lower image IO cost), and stronger edit fidelity — targeted at moving from “prototype/demo” to “production-friendly” image workflows.
Vs. Google’s Nano Banana Pro / Gemini image models: GPT-Image-1.5 and Google’s Nano Banana Pro / Gemini 3 family as close rivals — each has strengths in different prompt classes. OpenAI’s messaging emphasizes editing fidelity and iteration speed; Google’s offering has been praised for studio-level realism in some examples.
Vs. Qwen Image and other open/closed models: GPT-Image-1.5 outperforming Qwen Image on several edit and preservation metrics in single-turn evaluations, but differences narrow in multi-turn or other domain-specific tests.

Where GPT-Image-1.5’s strong

E-commerce product imaging: bulk variants, background swaps, consistent product catalogs from a single photo (brand/logo preservation).
Creative & marketing asset production: quick concept iterations, photorealistic mockups, controlled style transfers.
Photo retouching & editorial workflows: realistic clothing/hairstyle try-ons, selective retouching that preserves identity and lighting.
Design tooling integration: plug into design platforms or CMS for on-demand image variants (fidelity knobs help cost control).
Multi-step compositing pipelines: multi-image inputs allow compositing and reference-based generation for complex scenes.

How to access GPT Image 1.5 API

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.

Step 2: Send Requests to GPT Image 1.5 API

Select the “gpt-image-1.5” 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. base url is Images (https://api.cometapi.com/v1/images/generations) and [Image Editing]

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.

See also Gemini 3 Pro Preview API

FAQ

API

Copy a working endpoint and code example, then open the complete API reference when you need every parameter.

One API, production-ready model access

Authenticate once, call the model endpoint and keep the same billing and observability workflow across providers.

POST/v1/images/generations

Sample code and API for GPT Image 1.5

The gpt-image-1.5 API is a multimodal image model endpoint that accepts one or more image inputs (file identifiers or bytes) plus a text prompt and returns generated images or edited images. It supports:

POST

/v1/images/generations

# Set your API key if not set globally

# Create output/ folder
mkdir -p output

# Generate the image using gpt-image-1.5
response=$(curl -s https://api.cometapi.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-image-1.5",
    "prompt": "A cute baby sea otter",
    "n": 1,
    "size": "1024x1024"
  }')

# Extract base64 image data from response
if command -v jq &> /dev/null; then
  image_data=$(echo "$response" | jq -r '.data[0].b64_json')
else
  image_data=$(echo "$response" | sed -n 's/.*"b64_json":"\([^"]*\)".*/\1/p')
fi

if [ -n "$image_data" ] && [ "$image_data" != "null" ]; then
  # Decode base64 and save to file (macOS uses -D, Linux uses -d)
  echo "$image_data" | base64 -d > output/gpt-image-1.5-output.png 2>/dev/null || echo "$image_data" | base64 -D > output/gpt-image-1.5-output.png
  echo "Image saved to: output/gpt-image-1.5-output.png"
else
  echo "Error: Failed to generate image"
  echo "$response"
fi

cURL Code Example

# Set your API key if not set globally

# Create output/ folder
mkdir -p output

# Generate the image using gpt-image-1.5
response=$(curl -s https://api.cometapi.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-image-1.5",
    "prompt": "A cute baby sea otter",
    "n": 1,
    "size": "1024x1024"
  }')

# Extract base64 image data from response
if command -v jq &> /dev/null; then
  image_data=$(echo "$response" | jq -r '.data[0].b64_json')
else
  image_data=$(echo "$response" | sed -n 's/.*"b64_json":"\([^"]*\)".*/\1/p')
fi

if [ -n "$image_data" ] && [ "$image_data" != "null" ]; then
  # Decode base64 and save to file (macOS uses -D, Linux uses -d)
  echo "$image_data" | base64 -d > output/gpt-image-1.5-output.png 2>/dev/null || echo "$image_data" | base64 -D > output/gpt-image-1.5-output.png
  echo "Image saved to: output/gpt-image-1.5-output.png"
else
  echo "Error: Failed to generate image"
  echo "$response"
fi

Python Code Example

import base64
import os
from openai import OpenAI

# Set your API key if not set globally
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
client = OpenAI(api_key=COMETAPI_KEY, base_url="https://api.cometapi.com/v1")

# Create output/ folder
folder_path = "output"
os.makedirs(folder_path, exist_ok=True)

# Generate the image using gpt-image-1.5
result = client.images.generate(
    model="gpt-image-1.5",
    prompt="A cute baby sea otter",
    n=1,
    size="1024x1024"
)

# Save the image to a file
image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)
with open(os.path.join(folder_path, "gpt-image-1.5-output.png"), "wb") as f:
    f.write(image_bytes)

print("Image saved to: output/gpt-image-1.5-output.png")

JavaScript Code Example

import OpenAI from "openai";
import { writeFile, mkdir } from "fs/promises";
import path from "path";
import { fileURLToPath } from "url";

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

// Set your API key if not set globally
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: "https://api.cometapi.com/v1",
});

// Create output/ folder
const folderPath = path.join(__dirname, "../output");
await mkdir(folderPath, { recursive: true });

// Generate the image using gpt-image-1.5
const result = await client.images.generate({
  model: "gpt-image-1.5",
  prompt: "A cute baby sea otter",
  n: 1,
  size: "1024x1024",
});

// Save the image to a file
const imageBuffer = Buffer.from(result.data[0].b64_json, "base64");
await writeFile(path.join(folderPath, "gpt-image-1.5-output.png"), imageBuffer);

console.log("Image saved to: output/gpt-image-1.5-output.png");

Capabilities

Scan the model facts that matter before you choose an architecture or estimate production workload.

Supported capabilities

Features returned by the existing model API.

text-to-image

image-editing

Input and output

Inputs

text

Outputs

image

Production profile

Provider: OpenAI
Context: Model specific
Commercial use: Supported

Use cases

Use GPT Image 1.5 for production workflows that match its image capabilities, then compare alternatives before committing to a long-term integration.

Product visuals and campaign creative

Concept art and rapid visual exploration

Image editing, variation and asset production

Other models

Compare other models available through CometAPI for different quality, latency, capability and pricing trade-offs.

Open model comparison →

OpenAI

GPT Image 2.6

GPT Image 2.6 is OpenAI's image generation and editing model family, designed for professional visual creation, precise image manipulation, and more controllable creative workflows.

View model

Google

Nano Banana 2.1

Gemini Nano Banana 2.1 is Google's high-efficiency image-generation and conversational-editing model. It updates Nano Banana 2 while retaining Flash-level efficiency and adds improvements in visual quality, prompt adherence, multi-turn character consistency, text rendering, and infographic layout.

View model

Flux

Flux 3 Image

FLUX 3 Image is designed for creators and developers who need more control over the structure of a generated image than a simple text prompt may provide.

View model

Aliyun

Qwen-Image-3.0

Qwen-Image-3.0 is Alibaba Qwen's third-generation image generation model, designed to make AI-generated images more useful for real-world creative and design workflows rather than focusing only on visual aesthetics.

View model

Replicate

Black Forest Labs/FLUX 2 MAX

FLUX.2 [max] is the flagship, highest-quality variant of the FLUX.2 family from Black Forest Labs (BFL). It is positioned as a professional-grade text→image generation and image-editing model that focuses on maximal fidelity, prompt adherence, and editing consistency across characters, objects, lighting and color. BFL and partner registries describe FLUX.2 [max] as the top-tier FLUX.2 variant with features for multi-reference editing, grounded generation.

View model

Replicate

Black Forest Labs/FLUX 2 DEV

FLUX 2 DEV is the development-friendly version optimized for research, experimentation, and non-commercial applications. It provides developers with powerful image generation capabilities while maintaining a balance between quality and computational efficiency. Perfect for prototyping, academic research, and personal creative projects.

View model

Uptime

Review live heartbeat data, endpoint availability and observed response times before moving into production.

Uptime

Request success rate over the last 30 days, reflecting the reliability of each model provider. CometAPI monitors all connected providers in real time, 24/7.

Respond

35381msAvg. Response

Uptime

93.3%Avg. Uptime

Versions

Review available model identifiers before pinning a production integration.

gpt-image-1.5

gpt-image-1.5-2025-12-16

Updates

Follow meaningful availability, pricing and capability changes for GPT Image 1.5 without losing the stable model page.

Model changelog

One page that gets stronger over time.

Release notes, pricing changes, benchmark updates and migration guidance accumulate here while the canonical URL stays unchanged.

Dec 17, 2025

API availability confirmed

GPT Image 1.5 is available through the CometAPI model catalog and API documentation.

Current

Live data

Pricing and limits synced from the catalog

Price, context, availability and limits are treated as dynamic properties instead of being embedded in the page title or model identity.

Dec 17, 2025

Permanent model entity created

The provider and model slug form a durable canonical URL; future content and data updates remain on this page.

Keep exploring

Compare models and continue your research

OpenAI

Available

gpt-image-1.5

GPT Image 1.5 API

Starting price

$4.00 / 1M input tokens

Usage-based billing

API health

Available

Production endpoint

Response

Async ready

Observed API response

Released

Dec 17, 2025

OpenAI

Playground

Try GPT Image 1.5 with a real request, review its parameters and validate the output before integrating the API.

Pricing

Use the quick estimate above for a single run, then review the full CometAPI and official-price comparison.

First request

$0.0120

Estimated CometAPI usage cost

Ten requests

$0.1200

Estimated CometAPI usage cost

Fifteen requests

$0.1800

Estimated CometAPI usage cost

⇌

Credits conversion

1,000 credits = $1

Credits make budgets comparable across token, request and runtime billing. The USD amount remains the source of truth at checkout.

✓Current model in credits

Input

4,000

credits / 1M tokens

Output

8,000

credits / 1M tokens

Model	Comet Price (USD / M Tokens)	Official Price (USD / M Tokens)	Discount
gpt-image-1.5	Input: $4.00/M Output: $8.00/M	Input: $5.00/M Output: $10.00/M	-20%
gpt-image-1.5-2025-12-16	Input: $4.00/M Output: $8.00/M	Input: $5.00/M Output: $10.00/M	-20%

Model brief

A stable model identity for search and evaluation, paired with live catalog data that can change without rewriting the page's core SEO structure.

Stable identity

What is GPT Image 1.5?

Canonical model identity stays stable as pricing and limits change.

Live model data

Current catalog snapshot

Availability

Available

Starting price

$4.00 / 1M input tokens

Context

See capabilities

Catalog date

Dec 17, 2025

Overview

A practical overview of GPT Image 1.5, including important behavior and integration considerations.

What is the GPT-Image-1.5 API?

Text-to-image generation (create from prompt),
Image editing / in-painting / compositing (apply instructions to existing images, multiple image inputs allowed), and
Iterative, multi-turn editing workflows through the Responses API (enables “tweak & iterate” UIs).

Main features (practical)

Improved editability / multi-turn consistency: preserves character appearance, lighting and key visual attributes across iterative edits. This makes “same model, repeated edits” more reliable for workflows like product catalogs or brand assets.
Faster throughput — 4× speed improvements over GPT Image 1, aimed at lowering latency for iterative creative workflows.
Cost optimizations — image input/output costs reduced by about 20% vs. GPT Image 1, lowering per-image iteration costs for high-volume users.
Multi-image compositing & style referencing — accept multiple reference images to composite scenes or transfer style/lighting.
Quality/fidelity knobs — API parameters that trade off speed vs. fidelity (use lower quality for bulk generation; higher quality for production assets).
Multi-turn editing / Responses API integration — enables stepwise workflows (ask for changes, then “make tweaks” preserving state).

Technical capabilities

Text prompt limit (image models): up to 32,000 characters (note: OpenAI documents this as the text length allowance for GPT image models). Use this for long, constraint-heavy prompts.
Image inputs: accepts File IDs (preferred for multi-turn flows) or raw bytes; multiple images may be provided for compositing and reference.
Outputs: PNG/JPEG or platform default image artifacts returned by the API (or as attachments within ChatGPT). Outputs can include multiple candidate images and support iterative requests to refine an output.
Generation modes: text-to-image, image editing (inpaint/extend with instructions), and variants. Multi-turn editing supports “add/subtract/combine” style instructions.
Instruction-aware editing: models are optimized for instruction fidelity (preserving specified invariants like “do not change the logo”, “keep pose and lighting”). Prompt-engineering patterns (explicit invariants repeated each iteration) reduce semantic drift.

Benchmark performance

Leaderboard placement: One aggregate report cited GPT Image 1.5 leading text-to-image rankings with ~1264 points on an Artificial Analysis leaderboard, ahead of the next model by a measurable margin.
Task-level metrics (edit & preservation): a Microsoft Foundry summary of evaluation metrics shows GPT-Image-1.5 achieving near-perfect binary modification success (100% on a single-turn BinaryEval) and strong face-preservation scores (around 90% on AuraFace measures) in their comparison table versus competitors and previous OpenAI models. Those comparative metrics place GPT-Image-1.5 ahead of some rivals on preservation and edit fidelity.

GPT Image 1.5

How GPT-Image-1.5 compares to peers

Vs. GPT Image 1 (previous OpenAI generation): faster (up to 4×), cheaper (~20% lower image IO cost), and stronger edit fidelity — targeted at moving from “prototype/demo” to “production-friendly” image workflows.
Vs. Google’s Nano Banana Pro / Gemini image models: GPT-Image-1.5 and Google’s Nano Banana Pro / Gemini 3 family as close rivals — each has strengths in different prompt classes. OpenAI’s messaging emphasizes editing fidelity and iteration speed; Google’s offering has been praised for studio-level realism in some examples.
Vs. Qwen Image and other open/closed models: GPT-Image-1.5 outperforming Qwen Image on several edit and preservation metrics in single-turn evaluations, but differences narrow in multi-turn or other domain-specific tests.

Where GPT-Image-1.5’s strong

E-commerce product imaging: bulk variants, background swaps, consistent product catalogs from a single photo (brand/logo preservation).
Creative & marketing asset production: quick concept iterations, photorealistic mockups, controlled style transfers.
Photo retouching & editorial workflows: realistic clothing/hairstyle try-ons, selective retouching that preserves identity and lighting.
Design tooling integration: plug into design platforms or CMS for on-demand image variants (fidelity knobs help cost control).
Multi-step compositing pipelines: multi-image inputs allow compositing and reference-based generation for complex scenes.

How to access GPT Image 1.5 API

Step 2: Send Requests to GPT Image 1.5 API

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.

See also Gemini 3 Pro Preview API

FAQ

API

Copy a working endpoint and code example, then open the complete API reference when you need every parameter.

One API, production-ready model access

Authenticate once, call the model endpoint and keep the same billing and observability workflow across providers.

POST/v1/images/generations

Sample code and API for GPT Image 1.5

POST

/v1/images/generations

# Set your API key if not set globally

# Create output/ folder
mkdir -p output

# Generate the image using gpt-image-1.5
response=$(curl -s https://api.cometapi.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-image-1.5",
    "prompt": "A cute baby sea otter",
    "n": 1,
    "size": "1024x1024"
  }')

# Extract base64 image data from response
if command -v jq &> /dev/null; then
  image_data=$(echo "$response" | jq -r '.data[0].b64_json')
else
  image_data=$(echo "$response" | sed -n 's/.*"b64_json":"\([^"]*\)".*/\1/p')
fi

if [ -n "$image_data" ] && [ "$image_data" != "null" ]; then
  # Decode base64 and save to file (macOS uses -D, Linux uses -d)
  echo "$image_data" | base64 -d > output/gpt-image-1.5-output.png 2>/dev/null || echo "$image_data" | base64 -D > output/gpt-image-1.5-output.png
  echo "Image saved to: output/gpt-image-1.5-output.png"
else
  echo "Error: Failed to generate image"
  echo "$response"
fi

cURL Code Example

# Set your API key if not set globally

# Create output/ folder
mkdir -p output

# Generate the image using gpt-image-1.5
response=$(curl -s https://api.cometapi.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-image-1.5",
    "prompt": "A cute baby sea otter",
    "n": 1,
    "size": "1024x1024"
  }')

# Extract base64 image data from response
if command -v jq &> /dev/null; then
  image_data=$(echo "$response" | jq -r '.data[0].b64_json')
else
  image_data=$(echo "$response" | sed -n 's/.*"b64_json":"\([^"]*\)".*/\1/p')
fi

if [ -n "$image_data" ] && [ "$image_data" != "null" ]; then
  # Decode base64 and save to file (macOS uses -D, Linux uses -d)
  echo "$image_data" | base64 -d > output/gpt-image-1.5-output.png 2>/dev/null || echo "$image_data" | base64 -D > output/gpt-image-1.5-output.png
  echo "Image saved to: output/gpt-image-1.5-output.png"
else
  echo "Error: Failed to generate image"
  echo "$response"
fi

Python Code Example

import base64
import os
from openai import OpenAI

# Set your API key if not set globally
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
client = OpenAI(api_key=COMETAPI_KEY, base_url="https://api.cometapi.com/v1")

# Create output/ folder
folder_path = "output"
os.makedirs(folder_path, exist_ok=True)

# Generate the image using gpt-image-1.5
result = client.images.generate(
    model="gpt-image-1.5",
    prompt="A cute baby sea otter",
    n=1,
    size="1024x1024"
)

# Save the image to a file
image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)
with open(os.path.join(folder_path, "gpt-image-1.5-output.png"), "wb") as f:
    f.write(image_bytes)

print("Image saved to: output/gpt-image-1.5-output.png")

JavaScript Code Example

import OpenAI from "openai";
import { writeFile, mkdir } from "fs/promises";
import path from "path";
import { fileURLToPath } from "url";

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

// Set your API key if not set globally
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: "https://api.cometapi.com/v1",
});

// Create output/ folder
const folderPath = path.join(__dirname, "../output");
await mkdir(folderPath, { recursive: true });

// Generate the image using gpt-image-1.5
const result = await client.images.generate({
  model: "gpt-image-1.5",
  prompt: "A cute baby sea otter",
  n: 1,
  size: "1024x1024",
});

// Save the image to a file
const imageBuffer = Buffer.from(result.data[0].b64_json, "base64");
await writeFile(path.join(folderPath, "gpt-image-1.5-output.png"), imageBuffer);

console.log("Image saved to: output/gpt-image-1.5-output.png");

Capabilities

Scan the model facts that matter before you choose an architecture or estimate production workload.

Supported capabilities

Features returned by the existing model API.

text-to-image

image-editing

Input and output

Inputs

text

Outputs

image

Production profile

Provider: OpenAI
Context: Model specific
Commercial use: Supported

Use cases

Use GPT Image 1.5 for production workflows that match its image capabilities, then compare alternatives before committing to a long-term integration.

Product visuals and campaign creative

Concept art and rapid visual exploration

Image editing, variation and asset production

Other models

Compare other models available through CometAPI for different quality, latency, capability and pricing trade-offs.

Open model comparison →

OpenAI

GPT Image 2.6

GPT Image 2.6 is OpenAI's image generation and editing model family, designed for professional visual creation, precise image manipulation, and more controllable creative workflows.

FLUX 3 Image is designed for creators and developers who need more control over the structure of a generated image than a simple text prompt may provide.

Black Forest Labs/FLUX 2 MAX

View model

Replicate

Black Forest Labs/FLUX 2 DEV

View model

Uptime

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Uptime

Request success rate over the last 30 days, reflecting the reliability of each model provider. CometAPI monitors all connected providers in real time, 24/7.

Respond

35381msAvg. Response

Uptime

93.3%Avg. Uptime

Versions

Review available model identifiers before pinning a production integration.

gpt-image-1.5

gpt-image-1.5-2025-12-16

Updates

Follow meaningful availability, pricing and capability changes for GPT Image 1.5 without losing the stable model page.

Model changelog

One page that gets stronger over time.

Release notes, pricing changes, benchmark updates and migration guidance accumulate here while the canonical URL stays unchanged.

Dec 17, 2025

API availability confirmed

GPT Image 1.5 is available through the CometAPI model catalog and API documentation.

Current

Live data

Pricing and limits synced from the catalog

Price, context, availability and limits are treated as dynamic properties instead of being embedded in the page title or model identity.

Dec 17, 2025

Permanent model entity created

The provider and model slug form a durable canonical URL; future content and data updates remain on this page.

Keep exploring

GPT Image 1.5 API

Playground

Pricing

Model brief

What is GPT Image 1.5?

Current catalog snapshot

Overview

What is the GPT-Image-1.5 API?

Main features (practical)

Technical capabilities

Benchmark performance

How GPT-Image-1.5 compares to peers

Where GPT-Image-1.5’s strong

How to access GPT Image 1.5 API

Step 1: Sign Up for API Key

Step 2: Send Requests to GPT Image 1.5 API

Step 3: Retrieve and Verify Results

FAQ

How fast is GPT Image 1.5 compared to GPT Image 1?

Does GPT Image 1.5 support transparent backgrounds?

What is the maximum text prompt length for GPT Image 1.5?

How does GPT Image 1.5 compare to Google's Nano Banana Pro?

Does GPT Image 1.5 support multi-turn conversational editing?

Can GPT Image 1.5 use multiple reference images for compositing?

What resolutions and quality settings does GPT Image 1.5 support?

API

One API, production-ready model access

Sample code and API for GPT Image 1.5

cURL Code Example

Python Code Example

JavaScript Code Example

Capabilities

Use cases

Other models

Uptime

Uptime

Versions

Updates

One page that gets stronger over time.

API availability confirmed

Pricing and limits synced from the catalog

Permanent model entity created

Compare models and continue your research

GPT Image 1.5 API

Playground

Pricing

Model brief

What is GPT Image 1.5?

Current catalog snapshot

Overview

What is the GPT-Image-1.5 API?

Main features (practical)

Technical capabilities

Benchmark performance

How GPT-Image-1.5 compares to peers

Where GPT-Image-1.5’s strong

How to access GPT Image 1.5 API

Step 1: Sign Up for API Key

Step 2: Send Requests to GPT Image 1.5 API

Step 3: Retrieve and Verify Results

FAQ

How fast is GPT Image 1.5 compared to GPT Image 1?

Does GPT Image 1.5 support transparent backgrounds?

What is the maximum text prompt length for GPT Image 1.5?

How does GPT Image 1.5 compare to Google's Nano Banana Pro?

Does GPT Image 1.5 support multi-turn conversational editing?

Can GPT Image 1.5 use multiple reference images for compositing?

What resolutions and quality settings does GPT Image 1.5 support?

API

One API, production-ready model access

Sample code and API for GPT Image 1.5

cURL Code Example

Python Code Example

JavaScript Code Example

Capabilities

Use cases

Other models

Uptime

Uptime

Versions