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Stable Diffusion XL 1.0vs.Stable Diffusion 3 Medium

Which one is better?

In our own test, Stable Diffusion 3 Medium 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 XL 1.0: Infographic, first image from the fixed test run
Stable Diffusion XL 1.05 out of 100
Stable Diffusion 3 Medium: Infographic, first image from the fixed test run
Stable Diffusion 3 Medium34 out of 100

Result for “Infographic”:Stable Diffusion 3 Medium ahead

Prompt given to both modelsCreate a square German infographic titled SO FUNKTIONIERT PHOTOSYNTHESE. Show exactly four numbered steps in this order: 1 LICHT, 2 WASSER, 3 CO₂, 4 ZUCKER + SAUERSTOFF. Use a clean editorial science style with one plant cross-section, simple arrows, high contrast, legible labels, and no other text.

What the rating looks at: Numbers, labels, and visual organization.

“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

Stable Diffusion 3 Medium: fal, requested 1024x1024, n=1, seed=provider random, prompt expansion disabled, estimated cost $0.035000, generated Nov 2, 2026, 3:25 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: 26d3c3d3e687614e24dd12191246bc1d96c1576d31f9211840a3e02b64d4d507

Stable Diffusion 3 Medium image SHA 256: 23f00c74639e751fd6130d5f0e06539379c3a631d3f3cfde39c43e31973f5ef4

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

Stable Diffusion 3 Medium: fal, requested 1024x1024, n=1, seed=provider random, prompt expansion disabled, estimated cost $0.035000, generated Nov 2, 2026, 3:26 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: ebfe8d1c223478c94ff1973ab2600cd4f696b40b8c3388ca40f26f52c83afdb2

Stable Diffusion 3 Medium image SHA 256: d3247357eaa74b5b9157558cec7ffc4942c0a0fe09b5b7d661289d63c0359fbb

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

Stable Diffusion 3 Medium: fal, requested 1024x1024, n=1, seed=provider random, prompt expansion disabled, estimated cost $0.035000, generated Nov 2, 2026, 3:25 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: f59af9c84f6fbb3e4ca34bf87ebb0f7c088e8caa520fa4cdf815a96d1bffda83

Stable Diffusion 3 Medium image SHA 256: 7214318e9962af2466367b9ac75231f5b794a5db5a0b6d11d6e6f6a378cb28b6

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

Stable Diffusion 3 Medium: fal, requested 1024x1024, n=1, seed=provider random, prompt expansion disabled, estimated cost $0.035000, generated Nov 2, 2026, 3:25 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: c81e5d0d70afcb53fcffb51a0d548041fd0b33df300aed14b8ecd354aaaaec4e

Stable Diffusion 3 Medium image SHA 256: 9dd323604b3bfc1742a51a2ca225f9c0f8dfbe79f5fa68e6024015316c596a54

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

Stable Diffusion 3 Medium

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
13

Stable Diffusion XL 1.0

Rank 100 of 108

34

Stable Diffusion 3 Medium

Rank 78 of 108

Price per imagedollars through the API · lower is better
n/a

Stable Diffusion XL 1.0

no API price

n/a

Stable Diffusion 3 Medium

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.

Stable Diffusion 3 Medium

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

KennzahlStable Diffusion XL 1.0Stable Diffusion 3 Medium
Ratings
Arena ratingfrom votes by users, higher is bettern/an/a
Arena rankn/an/a
Arena votesmore votes, a safer ratingn/an/a
GraduallyBenchour own rating, 0 to 1001334
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition531
Product photographyMaterials, reflections, and fine details1326
Character and detailAnatomy, clothing, and spatial consistency2846
InfographicNumbers, labels, and visual organization534
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
Releasedn/aJun 12, 2024
Weightsopen means: runs locallyopenopen
LifecycleOlder open checkpoint; provider still lists it in its legacy model overviewno notice
AccessAPI, localAPI, local
Parametersnot published2 billion
Largest outputnot consistently publishednot consistently published
Plans in Germanynaming exactly this modeln/an/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) · Stable Diffusion 3 Medium 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 Stable Diffusion 3 Medium from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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