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MAI-Image-2.6vs.SDXL Turbo

Which one is better?

In our own test, MAI-Image-2.6 leads. SDXL Turbo has no arena rating yet. SDXL Turbo has no API price.

Test images

Same task, the first image of each. The task with the biggest difference is preselected.

MAI-Image-2.6: Product photography, first image from the fixed test run
MAI-Image-2.688 out of 100
SDXL Turbo: Product photography, first image from the fixed test run
SDXL Turbo3 out of 100

Result for “Product photography”:MAI-Image-2.6 ahead

Prompt given to both modelsCreate a square premium product photograph of a brushed titanium wristwatch standing upright on dark green marble. The watch has a cream dial, thin black hands set to 10:10, twelve distinct hour markers, a realistic crown, and a dark brown leather strap. Soft window light from the left, controlled reflections, shallow depth of field, no text, no logo, no extra objects.

What the rating looks at: Materials, reflections, and fine details.

“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

MAI-Image-2.6: openrouter, aspect ratio 1:1, provider default resolution, received 1024x1024, n=1, seed=provider random, actual cost $0.039287, generated Nov 1, 2026, 8:42 AM. 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

MAI-Image-2.6 image SHA 256: d35364051eca0758b88795df477d282641f6ca6892e81b904352e3fd5489ae69

SDXL Turbo image SHA 256: 9ee6443f4690649e93bdca408e5e8d317b312244636a3af47a02fe14eaf6c20c

Infographic

MAI-Image-2.6: openrouter, aspect ratio 1:1, provider default resolution, received 1024x1024, n=1, seed=provider random, actual cost $0.039317, generated Nov 1, 2026, 8:42 AM. 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

MAI-Image-2.6 image SHA 256: cdc9c16cd554a18da292c721b142e5d78dd042fdde2539f797612bfd9cd674ef

SDXL Turbo image SHA 256: 20395d858252aa131f235baa1f514039503a52dfec958c8f5b299db708bf4090

Product photography

MAI-Image-2.6: openrouter, aspect ratio 1:1, provider default resolution, received 1024x1024, n=1, seed=provider random, actual cost $0.039292, generated Nov 1, 2026, 8:41 AM. 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

MAI-Image-2.6 image SHA 256: a66f522e0ff2012b95dc3bc123216de7807206c9e91dd7711cd78eb34a234beb

SDXL Turbo image SHA 256: 75e5b85283110815e51a0470c937c3e42407244b50d918a3c0c54e10998a4b4c

Typography and layout

MAI-Image-2.6: openrouter, aspect ratio 1:1, provider default resolution, received 1024x1024, n=1, seed=provider random, actual cost $0.039252, generated Nov 1, 2026, 8:41 AM. 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

MAI-Image-2.6 image SHA 256: 48fa1551aee7dcd737179b5ae860d30562fbd234321b8d8ade334cb40291fb47

SDXL Turbo image SHA 256: 963088c72f75c98a95fd71be5f8d6e14fdf17061ae984f1109522a39be24ac76

The numbers at a glance

Arena ratingfrom votes by users · higher is better
1,331

MAI-Image-2.6

Rank 4 of 21

n/a

SDXL Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
68

MAI-Image-2.6

Rank 28 of 108

4

SDXL Turbo

Rank 105 of 108

Price per imagedollars through the API · lower is better
$0.039

MAI-Image-2.6

fairly cheap

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.

MAI-Image-2.6

Subscription
n/a No plan in Germany names exactly this model.
Via API
$0.039 per image, 100 images $3.89.

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.

Arena rating (LMArena) from Nov 6, 2026 · GraduallyBench from Nov 3, 2026 · API prices from Nov 6, 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.

KennzahlMAI-Image-2.6SDXL Turbo
Ratings
Arena ratingfrom votes by users, higher is better1,331n/a
Arena rankRank 4 of 21n/a
Arena votesmore votes, a safer rating38,071n/a
GraduallyBenchour own rating, 0 to 100684
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition623
Product photographyMaterials, reflections, and fine details883
Character and detailAnatomy, clothing, and spatial consistency633
InfographicNumbers, labels, and visual organization618
API price
Per imagelower is better$0.039n/a
100 images$3.89n/a
Profile
ReleasedJul 31, 2026n/a
Weightsopen means: runs locallyproprietaryopen
LifecyclePreview in Microsoft FoundryOlder open fast checkpoint; no active hosted API ID claimed in the reviewed model list
AccessAPIlocal
Parametersnot publishednot published
Largest output2,359,296 pixelsnot 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: MAI-Image-2.6 model source, status source (verified Sep 24, 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 MAI-Image-2.6 and SDXL Turbo from the same arena and category. Older model versions are not used as substitutes.

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