FLUX1.1 [pro] Ultravs.SDXL Turbo

Which one is better?

In our own test, FLUX1.1 [pro] Ultra 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.

FLUX1.1 [pro] Ultra: Character and detail, first image from the fixed test run — FLUX1.1 [pro] Ultra45 out of 100

SDXL Turbo: Character and detail, first image from the fixed test run — SDXL Turbo3 out of 100

Result for “Character and detail”:FLUX1.1 [pro] Ultra 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

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=3831910390, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 PM. Source

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=660064698563452219; 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, 6:23 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 0b97e1e3f33be2844c06cc18618fea633273ada7e9d6404f9769cdb8403ffbfc

SDXL Turbo image SHA 256: 9ee6443f4690649e93bdca408e5e8d317b312244636a3af47a02fe14eaf6c20c

Infographic

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=1664027293, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 PM. Source

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=6060807684445796734; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:23 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 2c7d24fcda220cf5eff966e1b857f11ad0e561f81ac9e4106ef1b4bd71686637

SDXL Turbo image SHA 256: 20395d858252aa131f235baa1f514039503a52dfec958c8f5b299db708bf4090

Product photography

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=291934417, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:49 PM. Source

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=4654331835179858246; 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, 6:22 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 7d497c35126a92de69af61e5721158a10f4e2acf88a8526dcdd0f8a9a571e028

SDXL Turbo image SHA 256: 75e5b85283110815e51a0470c937c3e42407244b50d918a3c0c54e10998a4b4c

Typography and layout

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=1909595532, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:49 PM. Source

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=1511362670078321145; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:21 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 0dfeffb6c3489b9ac2e1ae9100793320fa4f5eab779269de7aff3a4b768595f3

SDXL Turbo image SHA 256: 963088c72f75c98a95fd71be5f8d6e14fdf17061ae984f1109522a39be24ac76

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

FLUX1.1 [pro] Ultra

not in the arena

n/a

SDXL Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

FLUX1.1 [pro] Ultra

Rank 83 of 108

SDXL Turbo

Rank 105 of 108

Price per imagedollars through the API · lower is better

n/a

FLUX1.1 [pro] Ultra

no API price

n/a

SDXL Turbo

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.

FLUX1.1 [pro] Ultra

Subscription: No Black Forest Labs subscription includes this model. Through other providers from ≈ €9.54 a month (Krea Basic, with limited credits). 12 plans in Germany.
Via API: No API price known. Access: API.
Weights: unknown.

SDXL Turbo

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	FLUX1.1 [pro] Ultra	SDXL Turbo
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	31	4
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	22	3
Product photographyMaterials, reflections, and fine details	28	3
Character and detailAnatomy, clothing, and spatial consistency	45	3
InfographicNumbers, labels, and visual organization	28	8
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	unknown	open
Lifecycle	Separate Ultra API route / Ultra mode; no independent checkpoint established	Older open fast checkpoint; no active hosted API ID claimed in the reviewed model list
Access	API	local
Parameters	not published	not published
Largest output	not consistently published	not consistently published
Plans in Germanynaming exactly this model	12	n/a

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

Sources: FLUX1.1 [pro] Ultra model source, status source (verified Nov 1, 2026) · SDXL Turbo 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 FLUX1.1 [pro] Ultra and SDXL Turbo from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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