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Luma Uni-1.1vs.Sana-Sprint 1.6B 1024px

Which one is better?

In our own test, Luma Uni-1.1 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: Infographic, first image from the fixed test run
Luma Uni-1.189 out of 100
Sana-Sprint 1.6B 1024px: Infographic, first image from the fixed test run
Sana-Sprint 1.6B 1024px10 out of 100

Result for “Infographic”:Luma Uni-1.1 ahead

Prompt given to both modelsCreate a square German infographic titled SO FUNKTIONIERT PHOTOSYNTHESE. Show exactly four numbered steps in this order: 1 LICHT, 2 WASSER, 3 CO₂, 4 ZUCKER + SAUERSTOFF. Use a clean editorial science style with one plant cross-section, simple arrows, high contrast, legible labels, and no other text.

What the rating looks at: Numbers, labels, and visual organization.

“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: fal, aspect ratio 1:1, n=1, seed=provider random, Fal schema does not expose an output-resolution parameter; require square output of at least 1024px, estimated cost $0.042000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 1, 2026, 8:49 PM. Source

Sana-Sprint 1.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 889651570, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Luma Uni-1.1 image SHA 256: 4210462a5210fcde39e1f78167cb160cd3966176012d0ef2c187c6490d6a47e4

Sana-Sprint 1.6B 1024px image SHA 256: 1d77cacabeb38205299446bc6c5b80f38cf757d98f4251fc44c25340ab870dd9

Infographic

Luma Uni-1.1: fal, aspect ratio 1:1, n=1, seed=provider random, Fal schema does not expose an output-resolution parameter; require square output of at least 1024px, estimated cost $0.042000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 1, 2026, 8:50 PM. Source

Sana-Sprint 1.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 853526908, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a; an earlier request on 2026-11-01 was rejected before generation by the ZeroGPU quota, generated Nov 2, 2026, 2:30 PM. Source

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

Luma Uni-1.1 image SHA 256: fef94f2000cb22c90b2a147753ace395ee6c14f3e803e0cc88376556dd5267bc

Sana-Sprint 1.6B 1024px image SHA 256: da4ed66ab2f25ea33c81978bc687142d50f7f7d01db096169151e70f1648ec43

Product photography

Luma Uni-1.1: fal, aspect ratio 1:1, n=1, seed=provider random, Fal schema does not expose an output-resolution parameter; require square output of at least 1024px, estimated cost $0.042000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 1, 2026, 8:47 PM. Source

Sana-Sprint 1.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 178858232, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Luma Uni-1.1 image SHA 256: 9e31a8397f6dd1f0a09a0440510edcdbfbac5470f75a78ec6c6b67783099e5c2

Sana-Sprint 1.6B 1024px image SHA 256: 39284e75f1ffa7a286c193927441bca1bee31495f6cf67b4fd024a567a548b09

Typography and layout

Luma Uni-1.1: fal, aspect ratio 1:1, n=1, seed=provider random, Fal schema does not expose an output-resolution parameter; require square output of at least 1024px, estimated cost $0.042000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 1, 2026, 8:46 PM. Source

Sana-Sprint 1.6B 1024px: manual, 1:1, one request, first output, one image, provider-side randomize seed enabled, observed seed 37807657, native 1024x1024, 2 inference steps, guidance 4.5, no prompt enhancement, no reference images, exact checkpoint Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers, Space commit b42328123ed688df4bee46e52c60cc1dc62c045a, generated Nov 1, 2026, 9:42 PM. Source

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

Luma Uni-1.1 image SHA 256: 97710d52e2207b2bf7db070cf1dfa54af5ce79fd7a1fec12bdb1616c648c01f4

Sana-Sprint 1.6B 1024px image SHA 256: 5f4459e7adbe7d47fe3ba162ce8e13507b5ea6e3bb4beb5084c862df9ab9e933

The numbers at a glance

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

Luma Uni-1.1

not in the arena

n/a

Sana-Sprint 1.6B 1024px

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
66

Luma Uni-1.1

Rank 33 of 108

21

Sana-Sprint 1.6B 1024px

Rank 96 of 108

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

Luma Uni-1.1

no API price

n/a

Sana-Sprint 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

Subscription
No Luma AI subscription includes this model. Through other providers from €19.04 a month (Magnific Premium, with limited credits). 6 plans in Germany.
Via API
No API price known. Access: API.
Weights
unknown.

Sana-Sprint 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-1.1Sana-Sprint 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 1006621
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition6721
Product photographyMaterials, reflections, and fine details6027
Character and detailAnatomy, clothing, and spatial consistency4926
InfographicNumbers, labels, and visual organization8910
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
ReleasedMay 11, 2026Mar 22, 2025
Weightsopen means: runs locallyunknownopen
AccessAPIlocal
Parametersnot published1.6 billion
Largest outputnot consistently publishednot consistently published
Plans in Germanynaming exactly this model6n/a

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

Sources: Luma Uni-1.1 model source (verified Nov 1, 2026) · Sana-Sprint 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 and Sana-Sprint 1.6B 1024px from the same arena and category. Older model versions are not used as substitutes.

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