- Home
- Image model comparison
- Reve 2.1 vs. Stable Diffusion XL 1.0
Reve 2.1vs.Stable Diffusion XL 1.0
Which one is better?
In our own test, Reve 2.1 leads. Stable Diffusion XL 1.0 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.


Result for “Infographic”:Reve 2.1 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
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
Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=268378870826470633; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:07 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: 985a75b38642a9f0e5e0c0e0c67f1b7f67780d42bd2168fa24e9a7a7a94b0da6
Reve 2.1 image SHA 256: 29e9f7f38ed5c63dcfaab671a49fb9f4e9f82cd24b99134b87e1c22442822126
Stable Diffusion XL 1.0 image SHA 256: 26d3c3d3e687614e24dd12191246bc1d96c1576d31f9211840a3e02b64d4d507
Infographic
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
Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=5455008934753613262; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:08 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: ed65cb4e6a51e2336f8b149ad4cbb16e020f07d527ad94362e719d2dcf91d94f
Reve 2.1 image SHA 256: 30d157e85d75eb2ca1f71152d27f26d378ad8ea49b899d5f350ae0cda4e2bc59
Stable Diffusion XL 1.0 image SHA 256: ebfe8d1c223478c94ff1973ab2600cd4f696b40b8c3388ca40f26f52c83afdb2
Product photography
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
Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=490593220006868735; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:06 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: c67fd71e91304458a2feef5c91efa8677260fab0c0099a29a2c52cb579f5b2f3
Reve 2.1 image SHA 256: 1f91c3cb481151fb5165194b4edea2a46e786ca80e4ec3bdd888e3ba0016c510
Stable Diffusion XL 1.0 image SHA 256: f59af9c84f6fbb3e4ca34bf87ebb0f7c088e8caa520fa4cdf815a96d1bffda83
Typography and layout
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
Stable Diffusion XL 1.0: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/stable-diffusion-xl-base-1.0@462165984030d82259a11f4367a4eed129e94a7b; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0, seed=253938565953989943; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:05 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: 2e012c3d14ee5dd02203a94f394ca80a5038cdebd6032b25a8b8a221f2255419
Reve 2.1 image SHA 256: 84bcd1680fd0ae861ec66c21ab8f4cd79738bd093eb87ffe7283d9842c37cb1d
Stable Diffusion XL 1.0 image SHA 256: c81e5d0d70afcb53fcffb51a0d548041fd0b33df300aed14b8ecd354aaaaec4e
The numbers at a glance
Reve 2.1
Rank 6 of 21
Stable Diffusion XL 1.0
not in the arena
Reve 2.1
Rank 13 of 108
Stable Diffusion XL 1.0
Rank 100 of 108
Reve 2.1
no API price
Stable Diffusion XL 1.0
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: .
Stable Diffusion XL 1.0
- Subscription
- n/a No plan in Germany names exactly this model.
- Via API
- No API price known. Access: API, 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 | Stable Diffusion XL 1.0 |
|---|---|---|
| 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 | 13 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 54 | 5 |
| Product photographyMaterials, reflections, and fine details | 74 | 13 |
| Character and detailAnatomy, clothing, and spatial consistency | 80 | 28 |
| InfographicNumbers, labels, and visual organization | 85 | 5 |
| 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 | Older open checkpoint; provider still lists it in its legacy model overview |
| Access | API, local | |
| Parameters | not published | not published |
| 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) · Stable Diffusion XL 1.0 model source, status 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 Stable Diffusion XL 1.0 from the same arena and category. Older model versions are not used as substitutes.
More comparisons
Compare Reve 2.1 and Stable Diffusion XL 1.0 with the models people compare them with most often.