FLUX1.1 [pro]vs.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.
![FLUX1.1 [pro]: Character and detail, first image from the fixed test run](/_astro-img/2151775eb8b2037c/1024.avif)
Result for “Character and detail”:Kandinsky-5.0-T2I-Lite-SFT slightly ahead
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
FLUX1.1 [pro]: fal, requested 1024x1024, n=1, seed=1598804755, prompt expansion disabled, estimated cost $0.040000, generated Nov 1, 2026, 9:00 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
FLUX1.1 [pro] image SHA 256: b475e58b4513d0ed851a405764c795b380f352ddff2599324a6ddf4046a2ca83
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 8d193e702ad1aa0fccdb45f5d1474d60e21d455fa58d13470edd2796af0f2aed
Infographic
FLUX1.1 [pro]: fal, requested 1024x1024, n=1, seed=2834891197, prompt expansion disabled, estimated cost $0.040000, generated Nov 1, 2026, 9:00 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
FLUX1.1 [pro] image SHA 256: 2e27914d8784b0c4df1bb786934c4269230e1b2a6657fa500cb3cf46c3244041
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: e102016732db9e8e463504a83ac0770ff8a3c4c77918143d0f9dae8498c79101
Product photography
FLUX1.1 [pro]: fal, requested 1024x1024, n=1, seed=1611870596, prompt expansion disabled, estimated cost $0.040000, generated Nov 1, 2026, 9:00 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
FLUX1.1 [pro] image SHA 256: 4e45c833a1cfb178fdb2be4962709d5add987ae330bb860e739a934623327ad8
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: 73b31dc5a48059f7712c6a125ac4855f2401133101172c4bfbaa11b76c5ceee1
Typography and layout
FLUX1.1 [pro]: fal, requested 1024x1024, n=1, seed=22370095, prompt expansion disabled, estimated cost $0.040000, generated Nov 1, 2026, 9:00 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
FLUX1.1 [pro] image SHA 256: 30f27d636afd6c596e3314f7412ca3a0497be81362e72e40fbf8d8517adb80ab
Kandinsky-5.0-T2I-Lite-SFT image SHA 256: a84280dd219692f7b20722a37491d6788d1ecdc594f816fa1203981642501ab2
The numbers at a glance
FLUX1.1 [pro]
not in the arena
Kandinsky-5.0-T2I-Lite-SFT
not in the arena
FLUX1.1 [pro]
Rank 81 of 108
Kandinsky-5.0-T2I-Lite-SFT
Rank 79 of 108
FLUX1.1 [pro]
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.
FLUX1.1 [pro]
- Subscription
- No Black Forest Labs subscription includes this model. Through other providers from ≈ €9.54 a month (Krea Basic, with limited credits). 14 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 | FLUX1.1 [pro] | 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 | 33 | 34 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 42 | 21 |
| Product photographyMaterials, reflections, and fine details | 26 | 15 |
| Character and detailAnatomy, clothing, and spatial consistency | 39 | 65 |
| InfographicNumbers, labels, and visual organization | 24 | 33 |
| API price | ||
| Per imagelower is better | n/a | n/a |
| 100 images | n/a | n/a |
| Profile | ||
| Released | n/a | n/a |
| Weightsopen means: runs locally | unknown | open |
| Lifecycle | Older, still documented BFL text-to-image API route | no notice |
| Access | API | local |
| Parameters | not published | 6 billion |
| Largest output | not consistently published | not consistently published |
| Plans in Germanynaming exactly this model | 14 | n/a |
API prices for one image at 1,024 × 1,024 pixels according to Artificial Analysis.
Sources: FLUX1.1 [pro] model source, status 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 FLUX1.1 [pro] 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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