Stable Diffusion XL 1.0vs.Sana-Sprint 0.6B 1024px

Which one is better?

In our own test both are on par. 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 XL 1.0: Character and detail, first image from the fixed test run — Stable Diffusion XL 1.028 out of 100

Sana-Sprint 0.6B 1024px: Character and detail, first image from the fixed test run — Sana-Sprint 0.6B 1024px9 out of 100

Result for “Character and detail”:Stable Diffusion XL 1.0 slightly 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 XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=268378870826470633; 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, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:07 PM. Source

Sana-Sprint 0.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 1646387073, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_0.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: 26d3c3d3e687614e24dd12191246bc1d96c1576d31f9211840a3e02b64d4d507

Sana-Sprint 0.6B 1024px image SHA 256: 17356f29ad7fa9644e9683ec624d0c01ad56ff0c14d078db5f78f3b6bcf6a45e

Infographic

Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=5455008934753613262; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:08 PM. Source

Sana-Sprint 0.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 1798448399, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_0.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: ebfe8d1c223478c94ff1973ab2600cd4f696b40b8c3388ca40f26f52c83afdb2

Sana-Sprint 0.6B 1024px image SHA 256: efbab43ef1980109bff4084afe6162c4915e4fb55185617adaac5713f20b5e24

Product photography

Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=490593220006868735; 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, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:06 PM. Source

Sana-Sprint 0.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 520567323, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_0.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: f59af9c84f6fbb3e4ca34bf87ebb0f7c088e8caa520fa4cdf815a96d1bffda83

Sana-Sprint 0.6B 1024px image SHA 256: ac2d880a5b40924b518e25c61c5e077ffc9c5825f3eb896d733096ac6c631e46

Typography and layout

Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=253938565953989943; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:05 PM. Source

Sana-Sprint 0.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 1229099615, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_0.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: c81e5d0d70afcb53fcffb51a0d548041fd0b33df300aed14b8ecd354aaaaec4e

Sana-Sprint 0.6B 1024px image SHA 256: fd10095819c7746d6b52cc50e3d63f9d81eff271ad1edb4d3ba667a954098ac7

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Stable Diffusion XL 1.0

not in the arena

n/a

Sana-Sprint 0.6B 1024px

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Stable Diffusion XL 1.0

Rank 100 of 108

Sana-Sprint 0.6B 1024px

Rank 101 of 108

Price per imagedollars through the API · lower is better

n/a

Stable Diffusion XL 1.0

no API price

n/a

Sana-Sprint 0.6B 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 XL 1.0

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

Sana-Sprint 0.6B 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 XL 1.0	Sana-Sprint 0.6B 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	13	13
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	5	16
Product photographyMaterials, reflections, and fine details	13	19
Character and detailAnatomy, clothing, and spatial consistency	28	9
InfographicNumbers, labels, and visual organization	5	7
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	n/a	Mar 22, 2025
Weightsopen means: runs locally	open	open
Lifecycle	Older open checkpoint; provider still lists it in its legacy model overview	no notice
Access	API, local	local
Parameters	not published	0.6 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 XL 1.0 model source, status source (verified Nov 1, 2026) · Sana-Sprint 0.6B 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 XL 1.0 and Sana-Sprint 0.6B 1024px from the same arena and category. Older model versions are not used as substitutes.

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