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Qwen Image 2.1 Turbovs.Luma Uni-1.1

Which one is better?

In our own test both are on par. Neither is in the arena. Neither has an API price.

Same prompt, two images

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

Qwen Image 2.1 Turbo: Typography and layout, first image from the fixed test run
Qwen Image 2.1 Turbo39 out of 100
Luma Uni-1.1: Typography and layout, first image from the fixed test run
Luma Uni-1.164 out of 100

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

Both models receive the same archived prompt in exactly one request, and the first result counts. 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

Qwen Image 2.1 Turbo: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.018400, generated Nov 1, 2026, 8:31 PM. Source

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

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

Qwen Image 2.1 Turbo image SHA 256: 60c270da7b2ace74fcac4f55b962d4e01fae99265874d25857e2b461c00f3666

Luma Uni-1.1 image SHA 256: 4210462a5210fcde39e1f78167cb160cd3966176012d0ef2c187c6490d6a47e4

Infographic

Qwen Image 2.1 Turbo: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.018400, generated Nov 1, 2026, 8:31 PM. Source

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

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

Qwen Image 2.1 Turbo image SHA 256: 0650a13329baa39bb1923594082473a8138ecbe1ea95bb63017e7e1d76a7fafe

Luma Uni-1.1 image SHA 256: fef94f2000cb22c90b2a147753ace395ee6c14f3e803e0cc88376556dd5267bc

Product photography

Qwen Image 2.1 Turbo: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.018400, generated Nov 1, 2026, 8:30 PM. Source

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

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

Qwen Image 2.1 Turbo image SHA 256: 012d9320a2759329277e1e730e51da03aa4a0d992017a218228f88f07771dc08

Luma Uni-1.1 image SHA 256: 9e31a8397f6dd1f0a09a0440510edcdbfbac5470f75a78ec6c6b67783099e5c2

Typography and layout

Qwen Image 2.1 Turbo: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.018400, generated Nov 1, 2026, 8:30 PM. Source

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

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

Qwen Image 2.1 Turbo image SHA 256: a052bc14d0b36849b7bd6b38e368bf2bd11d68217ab675dbea3c58d8a62f34dd

Luma Uni-1.1 image SHA 256: 97710d52e2207b2bf7db070cf1dfa54af5ce79fd7a1fec12bdb1616c648c01f4

The numbers at a glance

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

Qwen Image 2.1 Turbo

not in the arena

n/a

Luma Uni-1.1

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
67

Qwen Image 2.1 Turbo

Rank 13 of 74

67

Luma Uni-1.1

Rank 14 of 74

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

Qwen Image 2.1 Turbo

no API price

n/a

Luma Uni-1.1

no API price

Ranks among the 22 image models with an arena rating and the 74 with a GraduallyBench run; prices compared with 28 models with an API price.

Qwen Image 2.1 Turbo

Subscription
n/a No plan in Germany names exactly this model.
Via API
No API price known. Access: API.
Weights
unknown.

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.

Subscriptions only count plans that name exactly this model. Subscription prices include VAT, API prices are in dollars.

GraduallyBench from Nov 1, 2026 · Subscription database from Sep 29, 2026 (34 days old)

All data side by side

The better value is bold. For ratings only when the gap is clear.

KennzahlQwen Image 2.1 TurboLuma Uni-1.1
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 1006767
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition3964
Product photographyMaterials, reflections, and fine details8459
Character and detailAnatomy, clothing, and spatial consistency5348
InfographicNumbers, labels, and visual organization9395
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
Releasedn/aMay 11, 2026
Weightsopen means: runs locallyunknownunknown
AccessAPIAPI
Parametersnot publishednot published
Largest output2Knot consistently published
Plans in Germanynaming exactly this modeln/a6

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

Sources: Qwen Image 2.1 Turbo model source (verified Nov 1, 2026) · Luma Uni-1.1 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 Qwen Image 2.1 Turbo and Luma Uni-1.1 from the same arena and category. Older model versions are not used as substitutes.

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