Stable Diffusion XL 1.0vs.Grok Imagine Image 1.0

Which one is better?

In our own test, Grok Imagine Image 1.0 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

Grok Imagine Image 1.0: Infographic, first image from the fixed test run — Grok Imagine Image 1.077 out of 100

Result for “Infographic”:Grok Imagine Image 1.0 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

Grok Imagine Image 1.0: fal, aspect ratio 1:1, n=1, seed=provider random, resolution 1K, estimated cost $0.020000, generated Nov 1, 2026, 9:30 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: 26d3c3d3e687614e24dd12191246bc1d96c1576d31f9211840a3e02b64d4d507

Grok Imagine Image 1.0 image SHA 256: f0a1722dd70365a05d18f1872dcf5761f358e13dca81e6ceafca69d17f658412

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

Grok Imagine Image 1.0: fal, aspect ratio 1:1, n=1, seed=provider random, resolution 1K, estimated cost $0.020000, generated Nov 1, 2026, 9:31 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: ebfe8d1c223478c94ff1973ab2600cd4f696b40b8c3388ca40f26f52c83afdb2

Grok Imagine Image 1.0 image SHA 256: 7dd25385835faf743c6e97b5a50ebcf5926cf94d862425177c25d8b27281ac8d

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

Grok Imagine Image 1.0: fal, aspect ratio 1:1, n=1, seed=provider random, resolution 1K, estimated cost $0.020000, generated Nov 1, 2026, 9:30 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: f59af9c84f6fbb3e4ca34bf87ebb0f7c088e8caa520fa4cdf815a96d1bffda83

Grok Imagine Image 1.0 image SHA 256: 95c5d4be59e6c115257f2414c513efd79bf7fd9ac69965ec04677eda2ec5a27a

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

Grok Imagine Image 1.0: fal, aspect ratio 1:1, n=1, seed=provider random, resolution 1K, estimated cost $0.020000, generated Nov 1, 2026, 9:30 PM. Source

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

Stable Diffusion XL 1.0 image SHA 256: c81e5d0d70afcb53fcffb51a0d548041fd0b33df300aed14b8ecd354aaaaec4e

Grok Imagine Image 1.0 image SHA 256: ab6dfd89aec95ebe7cfd2f3cacb4fbd66123306647c78d621d5c8c6325f3d7c5

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

Grok Imagine Image 1.0

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Stable Diffusion XL 1.0

Rank 100 of 108

Grok Imagine Image 1.0

Rank 12 of 108

Price per imagedollars through the API · lower is better

n/a

Stable Diffusion XL 1.0

no API price

n/a

Grok Imagine Image 1.0

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.

Grok Imagine Image 1.0

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

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	Grok Imagine Image 1.0
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	73
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	5	74
Product photographyMaterials, reflections, and fine details	13	81
Character and detailAnatomy, clothing, and spatial consistency	28	61
InfographicNumbers, labels, and visual organization	5	77
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	open	unknown
Lifecycle	Older open checkpoint; provider still lists it in its legacy model overview	no notice
Access	API, local	API
Parameters	not published	not published
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) · Grok Imagine Image 1.0 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 Grok Imagine Image 1.0 from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare Stable Diffusion XL 1.0 and Grok Imagine Image 1.0 with the models people compare them with most often.

Compare another matchup

First image modelSecond image model