Luma Uni-1.1vs.Kandinsky-5.0-T2I-Lite-SFT
Which one is better?
In our own test both are on par. 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.
Result for “Infographic”:Luma Uni-1.1 ahead
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
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
Luma Uni-1.1 image SHA 256: 4210462a5210fcde39e1f78167cb160cd3966176012d0ef2c187c6490d6a47e4
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 8d193e702ad1aa0fccdb45f5d1474d60e21d455fa58d13470edd2796af0f2aed
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
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
Luma Uni-1.1 image SHA 256: fef94f2000cb22c90b2a147753ace395ee6c14f3e803e0cc88376556dd5267bc
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: e102016732db9e8e463504a83ac0770ff8a3c4c77918143d0f9dae8498c79101
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
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
Luma Uni-1.1 image SHA 256: 9e31a8397f6dd1f0a09a0440510edcdbfbac5470f75a78ec6c6b67783099e5c2
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 73b31dc5a48059f7712c6a125ac4855f2401133101172c4bfbaa11b76c5ceee1
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
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
Luma Uni-1.1 image SHA 256: 97710d52e2207b2bf7db070cf1dfa54af5ce79fd7a1fec12bdb1616c648c01f4
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: a84280dd219692f7b20722a37491d6788d1ecdc594f816fa1203981642501ab2
The numbers at a glance
Luma Uni-1.1
not in the arena
Kandinsky-5.0-T2I-Lite-SFT
not in the arena
Luma Uni-1.1
Rank 33 of 108
Kandinsky-5.0-T2I-Lite-SFT
Rank 79 of 108
Luma Uni-1.1
no API price
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.
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.
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.
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.
| Kennzahl | Luma Uni-1.1 | Kandinsky-5.0-T2I-Lite-SFT |
|---|---|---|
| Ratings | ||
| Arena ratingfrom votes by users, higher is better | n/a | n/a |
| Arena rank | n/a | n/a |
| Arena votesmore votes, a safer rating | n/a | n/a |
| GraduallyBenchour own rating, 0 to 100 | 66 | 34 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 67 | 21 |
| Product photographyMaterials, reflections, and fine details | 60 | 15 |
| Character and detailAnatomy, clothing, and spatial consistency | 49 | 65 |
| InfographicNumbers, labels, and visual organization | 89 | 33 |
| API price | ||
| Per imagelower is better | n/a | n/a |
| 100 images | n/a | n/a |
| Profile | ||
| Released | May 11, 2026 | n/a |
| Weightsopen means: runs locally | unknown | open |
| Access | API | local |
| Parameters | not published | 6 billion |
| Largest output | not consistently published | not consistently published |
| Plans in Germanynaming exactly this model | 6 | n/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) · 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 Luma Uni-1.1 and Kandinsky-5.0-T2I-Lite-SFT from the same arena and category. Older model versions are not used as substitutes.
More comparisons
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