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MAI-Image-2.6vs.Kandinsky-5.0-T2I-Lite-SFT

Which one is better?

In our own test, MAI-Image-2.6 leads. Kandinsky-5.0-T2I-Lite-SFT has no arena rating yet. Kandinsky-5.0-T2I-Lite-SFT 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
Kandinsky-5.0-T2I-Lite-SFT: Product photography, first image from the fixed test run
Kandinsky-5.0-T2I-Lite-SFT15 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

Kandinsky-5.0-T2I-Lite-SFT: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-sft-Diffusers@c0158b5b20858d1fc02088db7ed4d805a296498b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=89463658088346984; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoders; float32 for transformer and CPU VAE; native tokenizer truncation: CLIP 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 8:12 PM. Source

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

MAI-Image-2.6 image SHA 256: d35364051eca0758b88795df477d282641f6ca6892e81b904352e3fd5489ae69

Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 8d193e702ad1aa0fccdb45f5d1474d60e21d455fa58d13470edd2796af0f2aed

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

Kandinsky-5.0-T2I-Lite-SFT: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-sft-Diffusers@c0158b5b20858d1fc02088db7ed4d805a296498b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=649868597087646690; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoders; float32 for transformer and CPU VAE, generated Nov 2, 2026, 8:21 PM. Source

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

MAI-Image-2.6 image SHA 256: cdc9c16cd554a18da292c721b142e5d78dd042fdde2539f797612bfd9cd674ef

Kandinsky-5.0-T2I-Lite-SFT image SHA 256: e102016732db9e8e463504a83ac0770ff8a3c4c77918143d0f9dae8498c79101

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

Kandinsky-5.0-T2I-Lite-SFT: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-sft-Diffusers@c0158b5b20858d1fc02088db7ed4d805a296498b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=4636200764941689006; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoders; float32 for transformer and CPU VAE; native tokenizer truncation: CLIP 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 8:02 PM. Source

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

MAI-Image-2.6 image SHA 256: a66f522e0ff2012b95dc3bc123216de7807206c9e91dd7711cd78eb34a234beb

Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 73b31dc5a48059f7712c6a125ac4855f2401133101172c4bfbaa11b76c5ceee1

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

Kandinsky-5.0-T2I-Lite-SFT: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-sft-Diffusers@c0158b5b20858d1fc02088db7ed4d805a296498b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=378697477899808767; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoders; float32 for transformer and CPU VAE; three local execution attempts: first aborted on an MPS dtype error; second returned an unsaved latent but the runner read the wrong output field; accepted first saved image after correcting that field with unchanged prompt, seed and FP32 sampling settings; lost latent content remains unknown, generated Nov 2, 2026, 7:52 PM. Source

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

MAI-Image-2.6 image SHA 256: 48fa1551aee7dcd737179b5ae860d30562fbd234321b8d8ade334cb40291fb47

Kandinsky-5.0-T2I-Lite-SFT image SHA 256: a84280dd219692f7b20722a37491d6788d1ecdc594f816fa1203981642501ab2

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

Kandinsky-5.0-T2I-Lite-SFT

not in the arena

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

MAI-Image-2.6

Rank 28 of 108

34

Kandinsky-5.0-T2I-Lite-SFT

Rank 79 of 108

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

MAI-Image-2.6

fairly cheap

n/a

Kandinsky-5.0-T2I-Lite-SFT

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.

Kandinsky-5.0-T2I-Lite-SFT

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-2.6Kandinsky-5.0-T2I-Lite-SFT
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 1006834
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition6221
Product photographyMaterials, reflections, and fine details8815
Character and detailAnatomy, clothing, and spatial consistency6365
InfographicNumbers, labels, and visual organization6133
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 Foundryno notice
AccessAPIlocal
Parametersnot published6 billion
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) · Kandinsky-5.0-T2I-Lite-SFT 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 MAI-Image-2.6 and Kandinsky-5.0-T2I-Lite-SFT from the same arena and category. Older model versions are not used as substitutes.

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