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Luma Uni-1.1 Maxvs.SANA-1.5 1.6B 1024px

Which one is better?

In our own test, Luma Uni-1.1 Max 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.

Luma Uni-1.1 Max: Typography and layout, first image from the fixed test run
Luma Uni-1.1 Max75 out of 100
SANA-1.5 1.6B 1024px: Typography and layout, first image from the fixed test run
SANA-1.5 1.6B 1024px3 out of 100

Result for “Typography and layout”:Luma Uni-1.1 Max 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

Luma Uni-1.1 Max: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.102000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Aug 14, 2026, 1:47 PM. Source

SANA-1.5 1.6B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers@b77948f2b4eed5c728e9b828ccff07f7427b43cc; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=4913908686846438154; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:32 PM. Source

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

Luma Uni-1.1 Max image SHA 256: 8034ca5627e1a256cdf1d06fc87b583d91d971d02edc9af7df52cd6721d3ea9c

SANA-1.5 1.6B 1024px image SHA 256: abc8d1fcb514ea7754211b79030abbf92ef83a61e546f19b217ccb06df0aaf45

Infographic

Luma Uni-1.1 Max: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.102000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Aug 14, 2026, 1:49 PM. Source

SANA-1.5 1.6B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers@b77948f2b4eed5c728e9b828ccff07f7427b43cc; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=1936313402304398258; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:33 PM. Source

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

Luma Uni-1.1 Max image SHA 256: 36dea214eb680804d4fea089eec3d4f10a4bf7b7a71c7a80f92313a37e8c2f73

SANA-1.5 1.6B 1024px image SHA 256: 828815adaab125d67312b64061f9b5a448558e9ac56ec9aa5ce8cf00cb63c481

Product photography

Luma Uni-1.1 Max: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.102000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Aug 14, 2026, 1:43 PM. Source

SANA-1.5 1.6B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers@b77948f2b4eed5c728e9b828ccff07f7427b43cc; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=1353667313865032696; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:32 PM. Source

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

Luma Uni-1.1 Max image SHA 256: 4890cdf8b858c5740124e3b2ba038b73f6a35decc7e3e3d920890462b6e89c2b

SANA-1.5 1.6B 1024px image SHA 256: a43c512ad071c0d7526e16f69874b653f073c532403114299c8fde43770a72c8

Typography and layout

Luma Uni-1.1 Max: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.102000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Aug 14, 2026, 2:40 PM. Source

SANA-1.5 1.6B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers@b77948f2b4eed5c728e9b828ccff07f7427b43cc; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=2028788407160516328; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled; two submissions: first attempt produced no image after a documented MPS VAE decoding crash; technical repeat kept the same prompt and seed, generated Nov 2, 2026, 5:31 PM. Source

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

Luma Uni-1.1 Max image SHA 256: d2a6162d544def0a283ed62f939b33252636d296a21142111851ecdedd2989d3

SANA-1.5 1.6B 1024px image SHA 256: 7c58a1c863d5b8d22d06ed159b89aa64d13cf9a44f7b3d4871683f491f0bb75c

The numbers at a glance

Arena ratingfrom votes by users · higher is better
n/a

Luma Uni-1.1 Max

not in the arena

n/a

SANA-1.5 1.6B 1024px

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
71

Luma Uni-1.1 Max

Rank 20 of 108

4

SANA-1.5 1.6B 1024px

Rank 107 of 108

Price per imagedollars through the API · lower is better
n/a

Luma Uni-1.1 Max

no API price

n/a

SANA-1.5 1.6B 1024px

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.

Luma Uni-1.1 Max

Subscription
n/a No plan in Germany names exactly this model.
Via API
No API price known. Access: API, Web app.

SANA-1.5 1.6B 1024px

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.

KennzahlLuma Uni-1.1 MaxSANA-1.5 1.6B 1024px
Ratings
Arena ratingfrom votes by users, higher is bettern/an/a
Arena rankn/an/a
Arena votesmore votes, a safer ratingn/an/a
GraduallyBenchour own rating, 0 to 100714
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition753
Product photographyMaterials, reflections, and fine details710
Character and detailAnatomy, clothing, and spatial consistency604
InfographicNumbers, labels, and visual organization797
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
ReleasedMay 2026Mar 16, 2025
Weightsopen means: runs locallyproprietaryopen
AccessAPI, Web applocal
Parametersnot published1.6 billion
Largest output2Knot 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: Luma Uni-1.1 Max model source (verified Aug 15, 2026) · SANA-1.5 1.6B 1024px 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 Luma Uni-1.1 Max and SANA-1.5 1.6B 1024px from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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