Stable Diffusion 3.5 Large Turbovs.SANA-1.5 4.8B 1024px

Which one is better?

In our own test, Stable Diffusion 3.5 Large Turbo 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.

Stable Diffusion 3.5 Large Turbo: Character and detail, first image from the fixed test run — Stable Diffusion 3.5 Large Turbo51 out of 100

SANA-1.5 4.8B 1024px: Character and detail, first image from the fixed test run — SANA-1.5 4.8B 1024px0 out of 100

Result for “Character and detail”:Stable Diffusion 3.5 Large Turbo 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

Stable Diffusion 3.5 Large Turbo: fal, image_size=square_hd, num_inference_steps=4, guidance_scale=0, n=1, seed=provider random, Estimate reserves 2 MP at Fal's $0.015 per MP rate, estimated cost $0.030000, generated Nov 2, 2026, 3:28 PM. Source

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=6914427587596023045; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:42 PM. Source

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

Stable Diffusion 3.5 Large Turbo image SHA 256: 312460ab73a4a22292bf6fbce099d86a22b0b8418f1516351f12f181b5574c76

SANA-1.5 4.8B 1024px image SHA 256: 97badf740db81367de7d6af73cc9313f1dfc4fe8383183ddbd9fc12cc67b35ee

Infographic

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=3447101042619426797; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:43 PM. Source

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

Stable Diffusion 3.5 Large Turbo image SHA 256: 16be803360e5a8025715fd221a0a623d1d68dc1ef38063d12c5abc1298e68d69

SANA-1.5 4.8B 1024px image SHA 256: 6c23b2df82d085e155c012c16915d04dd3a1aacdb78c9604eb74668309e07b38

Product photography

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=1122699157863902383; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:41 PM. Source

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

Stable Diffusion 3.5 Large Turbo image SHA 256: 1d9665660c7b05a58edc1b68c7f9d773ec4fbcaa41f15d3d691df764d5314b82

SANA-1.5 4.8B 1024px image SHA 256: 0ceaa96a83bc85d12c7f56b925226a346ee9b42f831fa5a9592edc4fc1e7ce81

Typography and layout

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=623973358981804157; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:40 PM. Source

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

Stable Diffusion 3.5 Large Turbo image SHA 256: e50fd19573ee42b2d6419b51f45bf29e04931ae1b583868d340fc05d973975ea

SANA-1.5 4.8B 1024px image SHA 256: 8371e0e35ad4472b71165cedd1940eb0339b19c24f801c3b956874c090a327fc

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Stable Diffusion 3.5 Large Turbo

not in the arena

n/a

SANA-1.5 4.8B 1024px

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Stable Diffusion 3.5 Large Turbo

Rank 88 of 108

SANA-1.5 4.8B 1024px

Rank 106 of 108

Price per imagedollars through the API · lower is better

n/a

Stable Diffusion 3.5 Large Turbo

no API price

n/a

SANA-1.5 4.8B 1024px

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.

Stable Diffusion 3.5 Large Turbo

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

SANA-1.5 4.8B 1024px

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	Stable Diffusion 3.5 Large Turbo	SANA-1.5 4.8B 1024px
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	27	4
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	26	8
Product photographyMaterials, reflections, and fine details	15	1
Character and detailAnatomy, clothing, and spatial consistency	51	0
InfographicNumbers, labels, and visual organization	17	6
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	Oct 22, 2024	Mar 16, 2025
Weightsopen means: runs locally	open	open
Access	API, local	local
Parameters	not published	4.8 billion
Largest output	not consistently published	not consistently published
Plans in Germanynaming exactly this model	n/a	n/a

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

Sources: Stable Diffusion 3.5 Large Turbo model source (verified Nov 1, 2026) · SANA-1.5 4.8B 1024px model 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 Stable Diffusion 3.5 Large Turbo and SANA-1.5 4.8B 1024px from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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