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Qwen Image 2.0 Provs.Luma Uni-1.1

Which one is better?

In our own test both are on par. Neither is in the arena. Luma Uni-1.1 has no API price.

Test images

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

Qwen Image 2.0 Pro: Character and detail, first image from the fixed test run
Qwen Image 2.0 Pro89 out of 100
Luma Uni-1.1: Character and detail, first image from the fixed test run
Luma Uni-1.149 out of 100

Result for “Character and detail”:Qwen Image 2.0 Pro ahead

Prompt given to both modelsCreate a square cinematic full-body portrait of a fictional bicycle courier waiting under a transparent umbrella at a rainy tram stop in Hamburg at blue hour. She wears a mustard raincoat, navy trousers, red sneakers, a silver helmet, and carries a teal messenger bag. Keep both hands visible, render the bicycle correctly, use realistic wet-street reflections, and include no readable brand names.

What the rating looks at: Anatomy, clothing, and spatial consistency.

“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

Qwen Image 2.0 Pro: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:21 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 2.0 Pro image SHA 256: 05f19da3e2d0eedb17d098c1b21abf8c83c663afa59083f0ce7a67a948e8a263

Luma Uni-1.1 image SHA 256: 4210462a5210fcde39e1f78167cb160cd3966176012d0ef2c187c6490d6a47e4

Infographic

Qwen Image 2.0 Pro: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:22 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 2.0 Pro image SHA 256: 003fbe859de5df62a4f49e3d590c00f5036e208149d81226d1835871fd1e0410

Luma Uni-1.1 image SHA 256: fef94f2000cb22c90b2a147753ace395ee6c14f3e803e0cc88376556dd5267bc

Product photography

Qwen Image 2.0 Pro: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:21 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 2.0 Pro image SHA 256: b811a440655cae766c039dfc8f9efb1756be5dce63ef22cd95deb1fe7dab6a3a

Luma Uni-1.1 image SHA 256: 9e31a8397f6dd1f0a09a0440510edcdbfbac5470f75a78ec6c6b67783099e5c2

Typography and layout

Qwen Image 2.0 Pro: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 2:00 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 2.0 Pro image SHA 256: 4eb4915afa71f6a8c76979dcecadd70beabd3869f11ca092a725fd7b6c87b4f2

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 2.0 Pro

not in the arena

n/a

Luma Uni-1.1

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
72

Qwen Image 2.0 Pro

Rank 17 of 108

66

Luma Uni-1.1

Rank 33 of 108

Price per imagedollars through the API · lower is better
$0.075

Qwen Image 2.0 Pro

fairly expensive

n/a

Luma Uni-1.1

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.

Qwen Image 2.0 Pro

Subscription
At Alibaba only in team or business plans, from ≈ €21.20 a month per seat (Token Plan Team Team Standard Seat). 3 plans in Germany.
Via API
$0.075 per image, 100 images $7.50.

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 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.

KennzahlQwen Image 2.0 ProLuma 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 1007266
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition8167
Product photographyMaterials, reflections, and fine details5860
Character and detailAnatomy, clothing, and spatial consistency8949
InfographicNumbers, labels, and visual organization6289
API price
Per imagelower is better$0.075n/a
100 images$7.50n/a
Profile
ReleasedApril 2026May 11, 2026
Weightsopen means: runs locallyproprietaryunknown
AccessAPIAPI
Parametersnot publishednot published
Largest output2,048 × 2,048 pixelsnot consistently published
Plans in Germanynaming exactly this model36

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

Sources: Qwen Image 2.0 Pro model source (verified Aug 15, 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 2.0 Pro and Luma Uni-1.1 from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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