GPT Image 1.5 Features: Generation, Editing, Inpainting, and Output Controls

GPT Image 1.5 is OpenAI's latest and most advanced image generation model, built for superior instruction following, text rendering, detailed editing, and real-world knowledge. It is the most capable model in the GPT Image family, and the one OpenAI recommends for the best overall output quality.

This article covers OpenAI GPT Image 1.5 features, including how each feature works in practice, and where the model's limitations sit.

GPT Image 1.5 Features Overview at a Glance

How GPT Image 1.5 Turns Prompts Into Visuals?

GPT Image 1.5 generates images from text prompts with superior instruction following compared to its predecessors in the DALL-E series. It understands the real-world knowledge and context behind a prompt rather than simply matching words to pixels, producing more accurate outputs across complex or compositionally demanding subjects.

Key generation capabilities:

• Generate a single image or multiple images in one request
• Returns
• base64-encoded image data by default, ready to save or display immediately
• Supports an auto quality setting where the model selects the best output quality based on the prompt

When using GPT Image 1.5, creators can leverage GPT Image 1.5 features for precise instruction-following and real-world context interpretation. ImagineArt's AI image generator provides a dedicated workspace for generation across all available models.

Recommended read: What is GPT Image 1.5?

Image Editing With a Prompt

GPT Image 1.5 supports image editing through a dedicated edit capability. You provide an existing image alongside a text prompt describing the change you want, and the model applies the edit while preserving unchanged areas.

You can also provide multiple images as references to generate a new composed image. Practical applications include:

• Combining individual product images into a styled arrangement without reshooting
• Placing a product into a new background context while preserving product detail
• Generating campaign imagery from existing brand assets without rebuilding compositions from scratch

For product teams working with reference-based imagery, ImagineArt AI product photo generator is the most relevant starting point for this type of multi-reference product photography workflow.

High Input Fidelity

GPT Image 1.5 supports a high input fidelity mode that preserves details from reference images more accurately in the output. This is particularly relevant when input images contain faces or logos that need to carry through the edit without degradation. With GPT Image 1.5, the first five input images benefit from higher fidelity preservation when this mode is enabled.

This makes it more reliable for:

• Brand asset work where logos and identity elements must remain visually intact
• Portrait editing where facial accuracy across the edit is a production requirement
• Product imagery where material texture and colour fidelity cannot be lost in the process

Inpainting: Edit One Region, Preserve Everything Else

Inpainting allows you to edit a targeted area of an existing image using a mask that indicates which region should be replaced, while everything outside that region remains completely unchanged.

An important distinction from DALL-E 2 is that masking with GPT Image 1.5 is entirely prompt-guided. The model uses the mask as directional guidance rather than treating its edges as hard pixel boundaries, which produces more natural-looking results at the transition between edited and preserved areas.

Common inpainting use cases:

• Replacing a product background in an e-commerce image without touching the product
• Removing or replacing a specific object in a scene
• Updating text or label elements on packaging without regenerating the full image
• Adding an element to an existing composition while preserving the surrounding context

For teams doing precision object-level editing, ImagineArt AI object remover and AI object replacer are dedicated tools that handle targeted removal and replacement as part of a broader editing workflow.

Multi-Turn Editing: Refine Images Step by Step

Multi-turn editing allows you to refine an image across a sequence of separate instructions, where each new instruction builds on the output of the previous one. Rather than describing an entire final result in a single prompt, you work toward it progressively through incremental changes.

This approach is well-suited for:

• Creative workflows where the desired output is not fully defined upfront
• Client feedback workflows where changes are applied across review rounds
• An iterative design exploration where early outputs inform what the next instruction should address

For teams building iterative creative production into a structured pipeline, the ImagineArt AI Workflow system supports automated pipelines that chain generation and editing steps into repeatable sequences.

Recommended read: How to Use GPT Image 1.5? | ImagineArt

Streaming: Preview Your Image While It Generates

GPT Image 1.5 supports streaming, which means you can receive partial previews of an image as it is being generated rather than waiting for the full output. Up to three partial images can be streamed during a single generation.

This is most useful when:

• You want early visibility into the direction of an output before it completes
• You are building interactive applications where progressive visual feedback improves user experience
• You want to cancel and adjust a prompt early if the partial output is clearly not going in the right direction

Transparent Backgrounds

GPT Image 1.5 supports transparent background generation, which produces images where the background is removed entirely rather than filled with a colour or scene. This is useful for assets that need to be placed on different backgrounds, layered into designs, or exported as standalone subjects.

Transparent background support:

• Available on PNG and WebP output formats only
• Works best when quality is set to medium or high
• Directly applicable to product photography, icon design, logo generation, and any asset intended for layered use

For creators producing assets for layered design work, the ImagineArt AI image editor and background changer are complementary tools for working with transparent or replaced backgrounds after generation.

Output Customisation: Size, Quality, Format and Compression Controls

GPT Image 1.5 gives you direct control over how output images are configured. All options below apply to GPT Image 1.5 specifically.

Size options:

• 1024x1024 (square)
• 1536x1024 (landscape)
• 1024x1536 (portrait)
• Auto (model selects based on the prompt)

Quality options:

• Low, Medium, High, or Auto
• Higher quality settings produce more detailed outputs, but take longer to generate and cost more
• Square images at standard quality are the fastest to generate

Output format options:

• PNG (default)
• JPEG (faster than PNG, recommended when generation speed matters)
• WebP

Compression:

• Available for JPEG and WebP formats
• Adjustable from 0 to 100 percent

For teams managing generation costs across different quality settings and output formats, ImagineArt's subscription plans page provides a full breakdown of credit costs and plan tiers to help plan production budgets accurately.

How Is Generation Cost Calculated?

GPT Image 1.5 generates images by producing image tokens, and both the time and cost of generation are proportional to the number of tokens required. Larger image sizes and higher quality settings produce more tokens and therefore cost more.

Token counts by quality setting:

The total cost of a generation is the sum of output image tokens, input text tokens for the prompt, and input image tokens if you are using the edits endpoint with reference images. If streaming is enabled, each partial image adds 100 image output tokens to the total.

Known Limitations of GPT Image 1.5 Features

OpenAI is transparent about the current limitations of GPT Image 1.5 features. Understanding these upfront helps set accurate expectations before building workflows around the model.

• Latency: Complex prompts may take up to 2 minutes to process. This is a known characteristic of high-quality generation and should be factored into time-sensitive production workflows
• Text rendering: Although significantly improved over the DALL-E series, the model can still struggle with precise text placement and clarity in some compositions
• Consistency: The model may occasionally struggle to maintain visual consistency for recurring characters or brand elements across multiple separate generations
• Composition control: Despite improved instruction following, the model may have difficulty placing elements precisely in structured or layout-sensitive compositions

For workflows where text rendering precision is critical, ImagineArt's AI image enhancer can be used to refine outputs after generation before they go to final delivery.

Achieve Better Results Faster

GPT Image 1.5 gives you the tools to produce high-quality visuals with total control. By delivering accurate text, seamless editing, and rapid output, it eliminates the common frustrations of digital creation.

Your time is valuable. Choose the tool that works as fast as you do and delivers professional results on the first try.