GPT-Image Compared: How to Choose Among 1.5 and 2.0 Text-to-Image and Image-to-Image

Introduction: The OpenAI GPT-Image Matrix

OpenAI’s GPT-Image line spans two generations—1.5 and 2.0—each with a text-to-image and an image-to-image workflow. On FuseAI Tools that yields four concrete modes: fast 1.5 routes for iteration, and v2 routes for long prompts, social aspect ratios, and 1K/2K/4K output.

The usual question is not “which brand” but which generation and which input type: should you draft on 1.5, deliver on 2.0, and do you start from text alone or from reference stills?

GPT-Image hub: /home/gpt-image

I. Snapshot: Four Models at a Glance

Model / route	Core function	Prompt limit	Output control	Reference images	Positioning
1.5 text-to-image	Text → image	3,000 chars	quality: medium / high	❌	Fast text-to-image
1.5 image-to-image	Image + text → image	3,000 chars	quality: medium / high	✅ (1 image)	Quick edits
2 text-to-image	Text → image	20,000 chars	resolution: 1K / 2K / 4K	❌	Pro text-to-image
2 image-to-image	Images + text → image	20,000 chars	resolution: 1K / 2K / 4K	✅ (up to 16)	Pro multi-reference edit

II. Four Models Deep Dive

Model 1: GPT-Image 1.5 text-to-image

Create stills from language with lightweight controls—ideal for concept boards and social drafts.

{
  "model": "gpt-image-1.5-text-to-image",
  "prompt": "Describe the image you want",
  "aspectRatio": "1:1",
  "quality": "medium"
}

Parameters:

Field	Options	Notes
aspectRatio	1:1, 2:3, 3:2	Three classic ratios; no 9:16
quality	medium, high	medium = balanced; high = slower, more detail

Best for: fast concepts, simple social tiles, low-friction experimentation.

Route: /home/gpt-image/text-to-image

Model 2: GPT-Image 1.5 image-to-image

Edit from a single reference still plus prompt—wardrobe swaps, background changes, light style shifts.

{
  "model": "gpt-image-1.5-image-to-image",
  "inputUrls": ["https://example.com/reference.jpg"],
  "prompt": "Change the outfit to a red dress; keep pose and expression",
  "aspectRatio": "3:2",
  "quality": "high"
}

Note: FuseAI Tools accepts one reference upload on the 1.5 image-to-image tab (JPG/PNG/WEBP, max 10MB).

Best for: product touch-ups, portrait edits, single-image guided variations.

Route: /home/gpt-image/image-to-image

Model 3: GPT-Image 2 text-to-image

Professional text-to-image with very long prompts and explicit pixel tiers.

{
  "model": "gpt-image-2-text-to-image",
  "prompt": "Cinematic cyberpunk city at night, neon rain reflections (up to 20000 characters)",
  "aspectRatio": "16:9",
  "resolution": "4K"
}

vs 1.5 text-to-image:

Contrast	1.5 text-to-image	2 text-to-image
Prompt limit	3,000 chars	20,000 chars
Output knob	quality	resolution (1K/2K/4K)
Aspect ratios	1:1, 2:3, 3:2	auto, 1:1, 9:16, 16:9, 4:3, 3:4
4K	❌	✅ (with rules below)

4K rules on FuseAI Tools:

1:1 cannot use 4K.
auto only allows 1K resolution.

Best for: posters, hero banners, print-minded stills, prompt-heavy art direction.

Route: /home/gpt-image/v2-text-to-image

Model 4: GPT-Image 2 image-to-image

High-resolution editing with up to sixteen reference URLs and the same v2 aspect-ratio and resolution stack.

{
  "model": "gpt-image-2-image-to-image",
  "prompt": "Blend wardrobe references into one editorial look, soft daylight",
  "inputUrls": [
    "https://example.com/ref-1.jpg",
    "https://example.com/ref-2.jpg"
  ],
  "aspectRatio": "9:16",
  "resolution": "2K"
}

vs 1.5 image-to-image: v2 adds 20k prompts, resolution tiers, social ratios, and multi-image input (up to 16). Use 1.5 when you only need a single quick edit; use v2 for complex fusion or 4K delivery.

Best for: multi-reference styling, campaign composites, high-res retouch pipelines.

Route: /home/gpt-image/v2-image-to-image

III. Cross-Model Comparison

3.1 Capability matrix

Feature	1.5 T2I	1.5 I2I	2 T2I	2 I2I
Text-to-image	✅	❌	✅	❌
Image-to-image	❌	✅	❌	✅
20,000-char prompt	❌	❌	✅	✅
4K output	❌	❌	✅	✅
Multi-reference (16)	❌	❌	❌	✅
auto aspect ratio	❌	❌	✅	✅
quality param	✅	✅	❌	❌
resolution param	❌	❌	✅	✅

3.2 Aspect ratio coverage

Ratio	1.5 series	2.0 series
1:1	✅	✅
2:3 / 3:2	✅	❌
16:9 / 9:16	❌	✅
4:3 / 3:4	❌	✅
auto	❌	✅ (1K only)

Takeaway: 1.5 favors classic photo ratios (2:3, 3:2). v2 targets social and cinematic frames (9:16, 16:9) plus optional auto sizing.

IV. Selection Decision Tree

What is your starting point?
|
|-- Text only (no reference image)
|   |-- Fast draft, simple brief -> 1.5 text-to-image
|   `-- Long brief, 4K, 9:16 or 16:9 -> 2 text-to-image
|
`-- Have reference image(s)
    |-- One image, quick edit -> 1.5 image-to-image
    `-- Many refs or 4K delivery -> 2 image-to-image

V. Practical Payload Examples

1.5 text-to-image

{
  "model": "gpt-image-1.5-text-to-image",
  "prompt": "An orange cat napping in warm sunlight, cozy home mood",
  "aspectRatio": "1:1",
  "quality": "high"
}

1.5 image-to-image

{
  "model": "gpt-image-1.5-image-to-image",
  "inputUrls": ["https://example.com/portrait.jpg"],
  "prompt": "Swap the outfit to a red dress; keep pose and expression",
  "aspectRatio": "3:2",
  "quality": "medium"
}

2 text-to-image (4K banner)

{
  "model": "gpt-image-2-text-to-image",
  "prompt": "Rain-soaked cyberpunk avenue, neon reflections, film still",
  "aspectRatio": "16:9",
  "resolution": "4K"
}

Reminder: do not pair 4K with 1:1 or auto.

2 image-to-image (multi-reference)

{
  "model": "gpt-image-2-image-to-image",
  "inputUrls": ["https://example.com/a.jpg", "https://example.com/b.jpg"],
  "prompt": "Merge styling cues from both references into one editorial frame",
  "aspectRatio": "9:16",
  "resolution": "2K"
}

VI. Final Recommendations

Use case	Model	Why
Quick concept still	1.5 text-to-image	Simple quality toggle, low friction
Single-photo edit	1.5 image-to-image	One reference, fast turnaround
Vertical social / hero banner	2 text-to-image	9:16 and 16:9 plus 4K tiers
Multi-image fusion	2 image-to-image	Up to 16 inputUrls
Long structured prompt	2.0 series	20,000-character ceiling

One-line playbook:

Daily drafts → 1.5 text-to-image or 1.5 image-to-image.
Final delivery → 2 text-to-image or 2 image-to-image.

1.5 and 2.0 are complementary: iterate cheaply on 1.5, then promote winners to v2 for resolution and ratio control. Open every mode from /home/gpt-image.