GPT Image 1.5vs.Stable Diffusion Turbo

Which one is better?

In our own test, GPT Image 1.5 leads. Stable Diffusion Turbo has no arena rating yet. Stable Diffusion Turbo has no API price.

Test images

Same task, the first image of each. The task with the biggest difference is preselected.

GPT Image 1.5: Character and detail, first image from the fixed test run — GPT Image 1.589 out of 100

Stable Diffusion Turbo: Character and detail, first image from the fixed test run — Stable Diffusion Turbo5 out of 100

Result for “Character and detail”:GPT Image 1.5 ahead

Prompt given to both modelsCreate a square cinematic full-body portrait of a fictional bicycle courier waiting under a transparent umbrella at a rainy tram stop in Hamburg at blue hour. She wears a mustard raincoat, navy trousers, red sneakers, a silver helmet, and carries a teal messenger bag. Keep both hands visible, render the bicycle correctly, use realistic wet-street reflections, and include no readable brand names.

What the rating looks at: Anatomy, clothing, and spatial consistency.

“Ahead”: better in all three rating rounds. “Slightly ahead”: a higher value, but not in every round.

Test protocol of the images

Each test attempt uses the same archived prompt and one request. The first output of that attempt counts. Repeats after technical test failures are disclosed for the affected images. Files are normalized to 1,024 × 1,024 pixels without cropping. Provider resolution, randomness, quality tier and prompt processing can still differ. The images are a practical visual test, not a reconstruction of the arena configuration.

Character and detail

GPT Image 1.5: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:17 PM. Source

Stable Diffusion Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sd-turbo@b261bac6fd2cf515557d5d0707481eafa0485ec2; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=5483236571890770311; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:17 PM. Source

Protocol gradually-image-comparison-v1. Prompt SHA 256: 985a75b38642a9f0e5e0c0e0c67f1b7f67780d42bd2168fa24e9a7a7a94b0da6

GPT Image 1.5 image SHA 256: 0dff52ccd39400ac66ac8870c9ea937512ff1474688e70118688f420c38c2296

Stable Diffusion Turbo image SHA 256: 291b69ba3d375bfa017c782f61521b705d67708ed5e1be9350d55d486ad6f1d1

Infographic

GPT Image 1.5: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:17 PM. Source

Stable Diffusion Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sd-turbo@b261bac6fd2cf515557d5d0707481eafa0485ec2; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=8161577731918994504; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:18 PM. Source

Protocol gradually-image-comparison-v1. Prompt SHA 256: ed65cb4e6a51e2336f8b149ad4cbb16e020f07d527ad94362e719d2dcf91d94f

GPT Image 1.5 image SHA 256: 1c9ff59c32621c8b48b002dacb0ae66487262280c7c0a5b3d6456c81b248ebe9

Stable Diffusion Turbo image SHA 256: 80a2687dbc408395b416994d4853332427d09fccead1a6229564cc25b32de7e6

Product photography

GPT Image 1.5: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:16 PM. Source

Stable Diffusion Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sd-turbo@b261bac6fd2cf515557d5d0707481eafa0485ec2; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=2124044582169182899; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:16 PM. Source

Protocol gradually-image-comparison-v1. Prompt SHA 256: c67fd71e91304458a2feef5c91efa8677260fab0c0099a29a2c52cb579f5b2f3

GPT Image 1.5 image SHA 256: 67cfa2f324447027ceb5f82e9446d40a1395b46ce425890a74606b4d97731cf6

Stable Diffusion Turbo image SHA 256: 13dcbe6eb77495317a03f3eed013c4358ae7466fca00d9f869e512279a8a2af6

Typography and layout

GPT Image 1.5: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 1:59 PM. Source

Stable Diffusion Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sd-turbo@b261bac6fd2cf515557d5d0707481eafa0485ec2; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=2303175353176269810; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:16 PM. Source

Protocol gradually-image-comparison-v1. Prompt SHA 256: 2e012c3d14ee5dd02203a94f394ca80a5038cdebd6032b25a8b8a221f2255419

GPT Image 1.5 image SHA 256: 6a4cec86850fd371b65274198e2bf630b3cf36a096f9fb953d4bfe17c3222ebe

Stable Diffusion Turbo image SHA 256: 7def19e4f4adf68244ff69e5873b9f465ecd158fb4abab0273443bfc3804438e

The numbers at a glance

Arena ratingfrom votes by users · higher is better

1,236

GPT Image 1.5

Rank 13 of 21

n/a

Stable Diffusion Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

GPT Image 1.5

Rank 29 of 108

Stable Diffusion Turbo

Rank 108 of 108

Price per imagedollars through the API · lower is better

$0.13

GPT Image 1.5

expensive

n/a

Stable Diffusion Turbo

no API price

Ranks among the 21 image models with an arena rating and the 108 with a GraduallyBench run; prices compared with 28 models with an API price.

GPT Image 1.5

Subscription: No OpenAI subscription includes this model. Through other providers from ≈ €6.36 a month (ElevenLabs Starter, with limited credits). 42 plans in Germany.
Via API: $0.13 per image, 100 images $13.30.

Stable Diffusion Turbo

Subscription: n/a No plan in Germany names exactly this model.
Via API: No API price known. Access: local.
License: Open weights.

Subscriptions only count plans that name exactly this model. Subscription prices include VAT, API prices are in dollars.

Arena rating (LMArena) from Nov 6, 2026 · GraduallyBench from Nov 3, 2026 · API prices from Nov 6, 2026 · Subscription database from Sep 29, 2026 (38 days old)

All data side by side

The better value is bold. For ratings only when the gap is clear.

Kennzahl	GPT Image 1.5	Stable Diffusion Turbo
Ratings
Arena ratingfrom votes by users, higher is better	1,236	n/a
Arena rank	Rank 13 of 21	n/a
Arena votesmore votes, a safer rating	173,798	n/a
GraduallyBenchour own rating, 0 to 100	68	3
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	60	0
Product photographyMaterials, reflections, and fine details	52	1
Character and detailAnatomy, clothing, and spatial consistency	89	5
InfographicNumbers, labels, and visual organization	72	5
API price
Per imagelower is better	$0.13	n/a
100 images	$13.30	n/a
Profile
Released	December 2025	n/a
Weightsopen means: runs locally	proprietary	open
Lifecycle	Marked as deprecated by OpenAI; removed from the API on December 1, 2026	Older open fast checkpoint; no active hosted API ID claimed in the reviewed model list
Access	API, Web app	local
Parameters	not published	not published
Largest output	1,536 × 1,024 pixels	not consistently published
Plans in Germanynaming exactly this model	42	n/a

API prices for one image at 1,024 × 1,024 pixels according to Artificial Analysis.

Sources: GPT Image 1.5 model source, status source (verified Aug 15, 2026) · Stable Diffusion Turbo model source, status source (verified Nov 1, 2026)

Arena ratings by category

From blind votes on LMArena. “Ahead” means the lead is clear.

No shared arena score in the stored snapshot

The stored benchmark database contains no measurement for GPT Image 1.5 and Stable Diffusion Turbo from the same arena and category. Older model versions are not used as substitutes.

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