Kling Image 3.0 Omnivs.Stable Diffusion XL 1.0

Which one is better?

In our own test, Kling Image 3.0 Omni 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.

Kling Image 3.0 Omni: Typography and layout, first image from the fixed test run — Kling Image 3.0 Omni93 out of 100

Stable Diffusion XL 1.0: Typography and layout, first image from the fixed test run — Stable Diffusion XL 1.05 out of 100

Result for “Typography and layout”:Kling Image 3.0 Omni 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

Kling Image 3.0 Omni: fal, aspect ratio 1:1, n=1, seed=provider random, Kling Omni 3, resolution 1K, single result, estimated cost $0.028000, generated Nov 1, 2026, 9:29 PM. Source

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

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

Kling Image 3.0 Omni image SHA 256: 5d326e157b4f3f7c54252761c0e49395f8e32244ba86f2e45d13eae353a9e807

Stable Diffusion XL 1.0 image SHA 256: 26d3c3d3e687614e24dd12191246bc1d96c1576d31f9211840a3e02b64d4d507

Infographic

Kling Image 3.0 Omni: fal, aspect ratio 1:1, n=1, seed=provider random, Kling Omni 3, resolution 1K, single result, estimated cost $0.028000, generated Nov 1, 2026, 9:30 PM. Source

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

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

Kling Image 3.0 Omni image SHA 256: e0ee4fab714481cc883130b588f90261b6acc24ff9da0f9e462e0ed6aafd1232

Stable Diffusion XL 1.0 image SHA 256: ebfe8d1c223478c94ff1973ab2600cd4f696b40b8c3388ca40f26f52c83afdb2

Product photography

Kling Image 3.0 Omni: fal, aspect ratio 1:1, n=1, seed=provider random, Kling Omni 3, resolution 1K, single result, estimated cost $0.028000, generated Nov 1, 2026, 9:29 PM. Source

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

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

Kling Image 3.0 Omni image SHA 256: b4d821252e19e1b7da304679af6a70353323cec9c80d36a769aaba1225b9274e

Stable Diffusion XL 1.0 image SHA 256: f59af9c84f6fbb3e4ca34bf87ebb0f7c088e8caa520fa4cdf815a96d1bffda83

Typography and layout

Kling Image 3.0 Omni: fal, aspect ratio 1:1, n=1, seed=provider random, Kling Omni 3, resolution 1K, single result, estimated cost $0.028000, generated Nov 1, 2026, 9:29 PM. Source

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

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

Kling Image 3.0 Omni image SHA 256: a9ab0938f07d6478dcbfd9f39e8dd17b8a5fe6216dfd4195789095cb6a6b9439

Stable Diffusion XL 1.0 image SHA 256: c81e5d0d70afcb53fcffb51a0d548041fd0b33df300aed14b8ecd354aaaaec4e

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Kling Image 3.0 Omni

not in the arena

n/a

Stable Diffusion XL 1.0

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Kling Image 3.0 Omni

Rank 52 of 108

Stable Diffusion XL 1.0

Rank 100 of 108

Price per imagedollars through the API · lower is better

n/a

Kling Image 3.0 Omni

no API price

n/a

Stable Diffusion XL 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.

Kling Image 3.0 Omni

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

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.

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	Kling Image 3.0 Omni	Stable Diffusion XL 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	61	13
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	93	5
Product photographyMaterials, reflections, and fine details	40	13
Character and detailAnatomy, clothing, and spatial consistency	82	28
InfographicNumbers, labels, and visual organization	30	5
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	Feb 5, 2026	n/a
Weightsopen means: runs locally	unknown	open
Lifecycle	no notice	Older open checkpoint; provider still lists it in its legacy model overview
Access	API	API, local
Parameters	not published	not published
Largest output	4K	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: Kling Image 3.0 Omni model source (verified Nov 1, 2026) · Stable Diffusion XL 1.0 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 Kling Image 3.0 Omni and Stable Diffusion XL 1.0 from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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