GPT Image 1.5: Complete Specifications, Pricing, API Access & Use Cases (2026)

What Is GPT Image 1.5?

GPT Image 1.5 is OpenAI’s previous-generation image generation and editing model, listed in OpenAI’s API model catalog for image generation and editing, with no officially confirmed context window and token-based API pricing as of July 2026. OpenAI’s model catalog identifies GPT Image 1.5 as a deprecated previous image generation model, while OpenAI’s deprecation documentation states that gpt-image-1.5 is scheduled for API removal on December 1, 2026, with GPT Image 2 recommended as the replacement.

The model is designed for text-guided image generation and image editing workflows. In practical terms, it is relevant for teams that need prompt-based creative drafts, product mockups, visual iteration, controlled edits, and API-driven image production. Teams comparing earlier OpenAI image models can also review GPT Image 1 to understand how OpenAI’s image-model family has evolved across generation and editing workflows.

For publication and production planning, GPT Image 1.5 should be treated as a documented but time-limited model. It can still be useful for existing workflows, short-term visual pipelines, migration testing, and cost comparison, but long-lived deployments should account for OpenAI’s announced December 1, 2026 API removal date.

What Are GPT Image 1.5’s Key Specifications and Pricing?

The main pricing point to verify before publication is the difference between OpenAI’s official image-input price and the Gate.AI model-card listing. OpenAI’s pricing page lists GPT Image 1.5 image input at \$8.00 per 1M tokens, while the Gate.AI model-card listing for this page records image input at \$10.00 per 1M. The article keeps those values separate to avoid merging provider pricing and platform listing data.

Teams building multimodal systems may compare GPT Image 1.5 pricing with broader OpenAI model pages such as GPT-5.5, GPT-4o mini, and o4-mini when planning cost, latency, and modality coverage across image, text, and reasoning workloads.

What Can GPT Image 1.5 Do That Makes It Useful in Production?

GPT Image 1.5 can generate images from text prompts. This is useful for early-stage creative concepts, marketing drafts, editorial visuals, product mockups, UI inspiration, and rapid visual exploration. The key production benefit is speed of iteration: teams can test multiple visual directions before committing design resources.

GPT Image 1.5 can also support image editing workflows. A team can provide an existing image and use natural-language instructions to revise or refine parts of it. This can be useful for adjusting backgrounds, testing product-placement ideas, changing visual style, or exploring alternate compositions. Human review remains necessary when edits involve faces, logos, brand assets, product claims, regulated categories, or identity-sensitive material.

The model may fit cost-aware image workflows because both OpenAI and the Gate.AI model-card listing provide token-based pricing information. This allows developers to estimate cost by prompt length, image input usage, output quality, and generated image volume. Cost should still be tested with real requests because image token usage can vary by size, quality, and endpoint behavior.

For teams using a model gateway, GPT Image 1.5 can be integrated through Gate.AI’s OpenAI-compatible image endpoint using the Gate.AI model-card ID openai/gpt-image-1.5. Gate.AI documentation confirms the OpenAI-compatible base URL, bearer-token authentication, and /images/generations path for synchronous image generation responses.

Teams that combine image, text, and video generation can use GPT Image 1.5 as part of a broader visual AI stack. For example, product teams may use image models for still assets while evaluating video-generation models such as Sora 2, Hailuo 2.3, Hailuo 02, Wan 2.6 T2V, and Seedance 2.0 for motion-based content workflows.

What Are GPT Image 1.5’s Supported Modalities?

GPT Image 1.5 should be understood primarily as an image model, not a general-purpose text, audio, or video model. For use cases that require broad multimodal reasoning, teams may compare it with models such as Gemini 2.5 Flash, Claude Haiku 4.5, and Llama 3.2 Vision, while keeping in mind that those models serve different roles from dedicated image generation systems.

Where Does GPT Image 1.5 Fall Short?

GPT Image 1.5 has a limited future API lifecycle. OpenAI states that older GPT Image models, including gpt-image-1.5, are scheduled for API removal on December 1, 2026. This is the most important limitation for production planning. New deployments should evaluate whether GPT Image 2 is a better long-term target.

Several technical details are not publicly confirmed. Official sources checked for this article do not confirm a traditional context window, knowledge cutoff, fine-tuning support, fixed public rate limits, JSON mode, or function-calling support for GPT Image 1.5. These fields should remain marked as unconfirmed rather than estimated.

Pricing can also require careful interpretation. OpenAI’s official pricing and the Gate.AI model-card listing should be treated as separate pricing references when they differ. Developers should confirm the price shown in their actual billing environment before launching high-volume image workflows.

This is a general AI limitation and is not model-specific unless stated by the provider: generated or edited images may include artifacts, inaccurate details, malformed text, inconsistent lighting, or unexpected changes to image regions that were not intended to change. Human review is important for commercial publishing, regulated use cases, identity-sensitive outputs, and brand-controlled assets.

GPT Image 1.5 should not be used as the sole decision-making system for legal, medical, financial, safety-critical, or identity-verification workflows. In those contexts, image generation or editing outputs should be treated as draft visual material and reviewed by qualified humans.

Teams that need stronger text reasoning, code generation, long-form analysis, or agentic workflows should evaluate separate text or reasoning models such as Claude Sonnet 4.6, Claude Opus 4.8, Grok 4.3, DeepSeek V4 Pro, or Qwen3.7 Max. Those comparisons are useful for system design, but they are not direct substitutes for a dedicated image-generation model.

What Is GPT Image 1.5 Best Used For?

GPT Image 1.5 is most relevant where the primary output is still imagery. If a workflow also requires text-heavy reasoning, retrieval, classification, or structured analysis, teams can pair image generation with separate language models such as Kimi K2.7 Code, MiniMax M3, GLM-5.2, or Mistral Small 4. This pairing can support workflows where one model generates visual assets while another model handles copy, planning, review, or automation.

How Does GPT Image 1.5 Compare to GPT Image 1 and GPT Image 2?

This comparison is neutral and scenario-qualified. It does not declare an overall winner because model choice depends on availability, price, output quality, latency, migration timing, and endpoint requirements.

For broader model selection, GPT Image 1.5 should be compared against models that match the task type. Image models should be evaluated against image-generation and editing needs, while text and reasoning models such as o3, DeepSeek R1, Gemini 3.5 Flash, and Claude Sonnet 5 should be evaluated for reasoning, coding, analysis, and agent workflows rather than direct image generation.

How Do I Access GPT Image 1.5 Through Gate.AI?

Gate.AI access for GPT Image 1.5 is represented by the Gate.AI model-card ID openai/gpt-image-1.5. Gate.AI documentation confirms an OpenAI-compatible API base URL at https://api.gate.ai/openai/v1, bearer-token authentication using a Gate.AI API key, and a synchronous text-to-image endpoint at /images/generations.

Use the exact model ID from the Gate.AI model card when making requests. Gate.AI’s documentation also notes that model IDs use a provider/model-name format, which aligns with openai/gpt-image-1.5.

Python Example

from openai import OpenAI
import os
client = OpenAI(
    api_key=os.environ["GATE_AI_API_KEY"],
    base_url="https://api.gate.ai/openai/v1",
)
response = client.images.generate(
    model="openai/gpt-image-1.5",
    prompt="A clean editorial product image of a matte black wireless speaker on a modern desk.",
    size="1024x1024",
    n=1,
)
print(response.data[0].url)

curl Example

curl -X POST "https://api.gate.ai/openai/v1/images/generations" \
  -H "Authorization: Bearer $GATE_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-image-1.5",
    "prompt": "A clean editorial product image of a matte black wireless speaker on a modern desk.",
    "size": "1024x1024",
    "n": 1
  }'

For production use, store the API key in an environment variable, avoid committing secrets, log request IDs and cost fields where available, and test representative prompts before estimating monthly spend. Because GPT Image 1.5 is scheduled for OpenAI API removal on December 1, 2026, teams should also test migration paths to GPT Image 2.

FAQs

What is GPT Image 1.5?
GPT Image 1.5 is OpenAI’s previous-generation image generation and editing model. It supports prompt-based image creation and image editing workflows, but OpenAI lists it as deprecated and scheduled for API removal on December 1, 2026.

How much does GPT Image 1.5 cost?
As of July 2026, OpenAI lists GPT Image 1.5 at \$5.00 per 1M text input tokens, \$8.00 per 1M image input tokens, \$10.00 per 1M text output tokens, and \$32.00 per 1M image output tokens. Gate.AI model-card pricing should be checked separately.

How do developers access GPT Image 1.5 through Gate.AI?
Developers can use the Gate.AI OpenAI-compatible image endpoint with the model-card ID openai/gpt-image-1.5, bearer-token authentication, and the /images/generations path.

Is GPT Image 1.5 suitable for new production systems?
It may fit existing workflows or short-term use, but OpenAI has scheduled gpt-image-1.5 for API removal on December 1, 2026. New production systems should evaluate GPT Image 2 as part of migration planning.