Reve 2.1vs.Kandinsky-5.0-T2I-Lite-Pretrain

Which one is better?

In our own test, Reve 2.1 leads. Kandinsky-5.0-T2I-Lite-Pretrain has no arena rating yet. Neither has an API price.

Test images

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

Reve 2.1: Character and detail, first image from the fixed test run — Reve 2.180 out of 100

Kandinsky-5.0-T2I-Lite-Pretrain: Character and detail, first image from the fixed test run — Kandinsky-5.0-T2I-Lite-Pretrain14 out of 100

Result for “Character and detail”:Reve 2.1 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

Reve 2.1: manual, Official Reve web app; Reve 2.1; chat creation; one request; 1:1 requested in prompt; first of two results; free plan; 2026-08-14; https://app.reve.com/model, source 4096x4096, stored 1024x1024 (Lanczos3 downscale), generated Aug 14, 2026, 4:23 PM. Source

Kandinsky-5.0-T2I-Lite-Pretrain: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-pretrain-Diffusers@0df26d22e3290e9778b0471457d651a51d83ae3d; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=893590444446603478; 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, 8:56 PM. Source

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

Reve 2.1 image SHA 256: 29e9f7f38ed5c63dcfaab671a49fb9f4e9f82cd24b99134b87e1c22442822126

Kandinsky-5.0-T2I-Lite-Pretrain image SHA 256: af9bdf8492b30fdaeb79b8f51d168a948d43ee1bbb29107f50a2f794db91a2e0

Infographic

Kandinsky-5.0-T2I-Lite-Pretrain: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-pretrain-Diffusers@0df26d22e3290e9778b0471457d651a51d83ae3d; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=6008496123190594626; 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, 9:08 PM. Source

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

Reve 2.1 image SHA 256: 30d157e85d75eb2ca1f71152d27f26d378ad8ea49b899d5f350ae0cda4e2bc59

Kandinsky-5.0-T2I-Lite-Pretrain image SHA 256: 6d1a99203c55f6a9ba5853aae207dfc5e264adc73b336253fae874f0243bd60e

Product photography

Kandinsky-5.0-T2I-Lite-Pretrain: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-pretrain-Diffusers@0df26d22e3290e9778b0471457d651a51d83ae3d; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=8854898730028115945; 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, 8:46 PM. Source

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

Reve 2.1 image SHA 256: 1f91c3cb481151fb5165194b4edea2a46e786ca80e4ec3bdd888e3ba0016c510

Kandinsky-5.0-T2I-Lite-Pretrain image SHA 256: 83169f5969d6ed636c5ba8ff01236290417a5942deec1089b4725cfeb0dc2b76

Typography and layout

Kandinsky-5.0-T2I-Lite-Pretrain: manual, local PyTorch 2.13.0, Diffusers 0.36.0; kandinskylab/Kandinsky-5.0-T2I-Lite-pretrain-Diffusers@0df26d22e3290e9778b0471457d651a51d83ae3d; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=9114026266664490789; 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, 8:36 PM. Source

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

Reve 2.1 image SHA 256: 84bcd1680fd0ae861ec66c21ab8f4cd79738bd093eb87ffe7283d9842c37cb1d

Kandinsky-5.0-T2I-Lite-Pretrain image SHA 256: 89cd2a1137d4d2ceb46c44b030f889bb3b14ac96ae190d2eb271dff02cfb5b74

The numbers at a glance

Arena ratingfrom votes by users · higher is better

1,300

Reve 2.1

Rank 6 of 21

n/a

Kandinsky-5.0-T2I-Lite-Pretrain

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Reve 2.1

Rank 13 of 108

Kandinsky-5.0-T2I-Lite-Pretrain

Rank 86 of 108

Price per imagedollars through the API · lower is better

n/a

Reve 2.1

no API price

n/a

Kandinsky-5.0-T2I-Lite-Pretrain

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.

Reve 2.1

Subscription: No Reve subscription includes this model. Through other providers from ≈ €12.72 a month (Recraft Basic, with limited credits). 3 plans in Germany.
Via API: No API price known. Access: .

Kandinsky-5.0-T2I-Lite-Pretrain

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.

Arena rating (LMArena) from Nov 6, 2026 · 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	Reve 2.1	Kandinsky-5.0-T2I-Lite-Pretrain
Ratings
Arena ratingfrom votes by users, higher is better	1,300	n/a
Arena rank	Rank 6 of 21	n/a
Arena votesmore votes, a safer rating	8,237	n/a
GraduallyBenchour own rating, 0 to 100	73	28
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	54	16
Product photographyMaterials, reflections, and fine details	74	58
Character and detailAnatomy, clothing, and spatial consistency	80	14
InfographicNumbers, labels, and visual organization	85	23
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	July 2026	n/a
Weightsopen means: runs locally	proprietary	open
Lifecycle	Retired; no new image or video generation after September 27, 2026. Existing assets can be downloaded until October 31, 2026	no notice
Access		local
Parameters	not published	6 billion
Largest output	4K	not consistently published
Plans in Germanynaming exactly this model	3	n/a

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

Sources: Reve 2.1 model source, status source (verified Aug 15, 2026) · Kandinsky-5.0-T2I-Lite-Pretrain 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 Reve 2.1 and Kandinsky-5.0-T2I-Lite-Pretrain from the same arena and category. Older model versions are not used as substitutes.

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Test images

The numbers at a glance

Reve 2.1

Kandinsky-5.0-T2I-Lite-Pretrain

All data side by side

Arena ratings by category

No shared arena score in the stored snapshot

More comparisons

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