Seedream 4.5vs.Stable Diffusion Turbo

Which one is better?

In our own test, Seedream 4.5 leads. Neither is in the arena. Neither has an API price.

Test images

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

Seedream 4.5: Typography and layout, first image from the fixed test run — Seedream 4.584 out of 100

Stable Diffusion Turbo: Typography and layout, first image from the fixed test run — Stable Diffusion Turbo0 out of 100

Result for “Typography and layout”:Seedream 4.5 ahead

Prompt given to both modelsCreate a square editorial poster for an imaginary night train called MONDFALTER. Show the exact German headline MONDFALTER and the exact subline BERLIN NACH LISSABON. Use a restrained midnight-blue and warm-cream palette, one stylized moth, strong Swiss-grid typography, generous negative space, and no additional words or logos.

What the rating looks at: Legible text, hierarchy, and composition.

“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

Seedream 4.5: fal, requested native 2048x2048 square, n=1, seed=607017308, estimated cost $0.040000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 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

Seedream 4.5 image SHA 256: 614d5b810be9f7cc54c999fb930e5bb1a7a5b58f7211a3b71aa92e83a360cf78

Stable Diffusion Turbo image SHA 256: 291b69ba3d375bfa017c782f61521b705d67708ed5e1be9350d55d486ad6f1d1

Infographic

Seedream 4.5: fal, requested native 2048x2048 square, n=1, seed=467481828, estimated cost $0.040000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:51 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

Seedream 4.5 image SHA 256: ec1e2be1080670edf050cff00a094ff471c1b480a11a3922cf8c25f0ef0f6a5e

Stable Diffusion Turbo image SHA 256: 80a2687dbc408395b416994d4853332427d09fccead1a6229564cc25b32de7e6

Product photography

Seedream 4.5: fal, requested native 2048x2048 square, n=1, seed=1880157282, estimated cost $0.040000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 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

Seedream 4.5 image SHA 256: 48a36dede8c680fa8e2231ac33a95b1417dcded96ad753c98218cc78ed96a65b

Stable Diffusion Turbo image SHA 256: 13dcbe6eb77495317a03f3eed013c4358ae7466fca00d9f869e512279a8a2af6

Typography and layout

Seedream 4.5: fal, requested native 2048x2048 square, n=1, seed=775629027, estimated cost $0.040000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 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

Seedream 4.5 image SHA 256: 62d4e5b0b3c9ca5a55952dc2c5aca878ed687c76f302ad632136bd3e6bee3872

Stable Diffusion Turbo image SHA 256: 7def19e4f4adf68244ff69e5873b9f465ecd158fb4abab0273443bfc3804438e

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Seedream 4.5

not in the arena

n/a

Stable Diffusion Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Seedream 4.5

Rank 64 of 108

Stable Diffusion Turbo

Rank 108 of 108

Price per imagedollars through the API · lower is better

n/a

Seedream 4.5

no API price

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.

Seedream 4.5

Subscription: No ByteDance / Volcengine subscription includes this model. Through other providers from ≈ €6.36 a month (ElevenLabs Starter, with limited credits). 39 plans in Germany.
Via API: No API price known. Access: API, Web app.
Weights: unknown.

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.

GraduallyBench from Nov 3, 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	Seedream 4.5	Stable Diffusion Turbo
Ratings
Arena ratingfrom votes by users, higher is better	n/a	n/a
Arena rank	n/a	n/a
Arena votesmore votes, a safer rating	n/a	n/a
GraduallyBenchour own rating, 0 to 100	48	3
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	84	0
Product photographyMaterials, reflections, and fine details	44	1
Character and detailAnatomy, clothing, and spatial consistency	37	5
InfographicNumbers, labels, and visual organization	27	5
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	n/a	n/a
Weightsopen means: runs locally	unknown	open
Lifecycle	Still-listed T2I/I2I model ID; Ark marks it as pending shutdown without giving a date in the reviewed source	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	not consistently published	not consistently published
Plans in Germanynaming exactly this model	39	n/a

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

Sources: Seedream 4.5 model source, status source (verified Nov 1, 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 Seedream 4.5 and Stable Diffusion Turbo from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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