Nano Banana 2.1vs.Boogu-Image-0.1-Base
Which one is better?
In our own test, Nano Banana 2.1 leads. 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 “Typography and layout”:Nano Banana 2.1 ahead
What the rating looks at: Legible text, hierarchy, and composition.
“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
Nano Banana 2.1: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.036408, generated Nov 1, 2026, 9:40 PM. Source
Boogu-Image-0.1-Base: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Base@334ad7e5c6343d33308b306127e047b133e86926; native 1024x1024, 1:1; one request, first output; steps=50, guidance=4.0, seed=895870850114772015; mps; native PyTorch fallback is enabled by PYTORCH_ENABLE_MPS_FALLBACK=1; actual CPU operation use is not measured; bfloat16; upstream boogu-project/Boogu-Image@9b327526b1053e1f27f1bd0ae36b20ce2c39cb9e; reviewed MPS device allowlist and empty-reference self-attention only on original CPU SDPA, unchanged arguments and dtype; nonempty attention remains on MPS; no CUDA numeric equivalence claimed; native VAE input saved after scaling and shift, decoded float output finite before native same-size interpolation; native instruction template without rewriting; original Base sampling, no Turbo DMD inference, generated Nov 2, 2026, 11:56 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: 985a75b38642a9f0e5e0c0e0c67f1b7f67780d42bd2168fa24e9a7a7a94b0da6
Nano Banana 2.1 image SHA 256: f89e3f52678670058ce0e1e9b0b5b6ec084e25a212491b5025e76d7525fb8707
Boogu-Image-0.1-Base image SHA 256: 5ca2782a121b2ffdd620953a4453df06769a5d51778c7980e1cddc8b8e79e0dd
Infographic
Nano Banana 2.1: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.036560, generated Nov 1, 2026, 9:40 PM. Source
Boogu-Image-0.1-Base: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Base@334ad7e5c6343d33308b306127e047b133e86926; native 1024x1024, 1:1; one request, first output; steps=50, guidance=4.0, seed=7796952798756533109; mps; native PyTorch fallback is enabled by PYTORCH_ENABLE_MPS_FALLBACK=1; actual CPU operation use is not measured; bfloat16; upstream boogu-project/Boogu-Image@9b327526b1053e1f27f1bd0ae36b20ce2c39cb9e; reviewed MPS device allowlist and empty-reference self-attention only on original CPU SDPA, unchanged arguments and dtype; nonempty attention remains on MPS; no CUDA numeric equivalence claimed; native VAE input saved after scaling and shift, decoded float output finite before native same-size interpolation; native instruction template without rewriting; original Base sampling, no Turbo DMD inference, generated Nov 3, 2026, 12:04 AM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: ed65cb4e6a51e2336f8b149ad4cbb16e020f07d527ad94362e719d2dcf91d94f
Nano Banana 2.1 image SHA 256: ce5c4b7af2575ccf9964cfeea2e4f0bb75cdad21aea29c4201e693fa307e435b
Boogu-Image-0.1-Base image SHA 256: 7b4a49a08dcb03776edaf18345ffe94ee7ae0293be8b3611bf676aa6c76c6405
Product photography
Nano Banana 2.1: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.036546, generated Nov 1, 2026, 9:39 PM. Source
Boogu-Image-0.1-Base: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Base@334ad7e5c6343d33308b306127e047b133e86926; native 1024x1024, 1:1; one request, first output; steps=50, guidance=4.0, seed=6866357448264114469; mps; native PyTorch fallback is enabled by PYTORCH_ENABLE_MPS_FALLBACK=1; actual CPU operation use is not measured; bfloat16; upstream boogu-project/Boogu-Image@9b327526b1053e1f27f1bd0ae36b20ce2c39cb9e; reviewed MPS device allowlist and empty-reference self-attention only on original CPU SDPA, unchanged arguments and dtype; nonempty attention remains on MPS; no CUDA numeric equivalence claimed; native VAE input saved after scaling and shift, decoded float output finite before native same-size interpolation; native instruction template without rewriting; original Base sampling, no Turbo DMD inference, generated Nov 2, 2026, 11:47 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: c67fd71e91304458a2feef5c91efa8677260fab0c0099a29a2c52cb579f5b2f3
Nano Banana 2.1 image SHA 256: 289b144f7d5348e9324d229e5508d5698c09035f2cbdea474845a84b852e859e
Boogu-Image-0.1-Base image SHA 256: d0e66f73a26844f514cb97bbbd69bb8f4bf39bd875ac8fca0f04989949a64478
Typography and layout
Nano Banana 2.1: openrouter, aspect ratio 1:1, resolution 1K, n=1, seed=provider random, actual cost $0.036497, generated Nov 1, 2026, 9:39 PM. Source
Boogu-Image-0.1-Base: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Base@334ad7e5c6343d33308b306127e047b133e86926; native 1024x1024, 1:1; one request, first output; steps=50, guidance=4.0, seed=5844980489998903917; mps; native PyTorch fallback is enabled by PYTORCH_ENABLE_MPS_FALLBACK=1; actual CPU operation use is not measured; bfloat16; upstream boogu-project/Boogu-Image@9b327526b1053e1f27f1bd0ae36b20ce2c39cb9e; reviewed MPS device allowlist and empty-reference self-attention only on original CPU SDPA, unchanged arguments and dtype; nonempty attention remains on MPS; no CUDA numeric equivalence claimed; native VAE input saved after scaling and shift, decoded float output finite before native same-size interpolation; native instruction template without rewriting; original Base sampling, no Turbo DMD inference, generated Nov 2, 2026, 11:36 PM. Source
Protocol gradually-image-comparison-v1. Prompt SHA 256: 2e012c3d14ee5dd02203a94f394ca80a5038cdebd6032b25a8b8a221f2255419
Nano Banana 2.1 image SHA 256: d27b58baa4115177a46fae2d71e258c5f4de9243fc66df93983ef6127df2f320
Boogu-Image-0.1-Base image SHA 256: b9abc77788966e5c8425e7a94c12632b4e4ec11e6d41c7afd0e1acdc37602db3
The numbers at a glance
Nano Banana 2.1
not in the arena
Boogu-Image-0.1-Base
not in the arena
Nano Banana 2.1
Rank 36 of 108
Boogu-Image-0.1-Base
Rank 103 of 108
Nano Banana 2.1
no API price
Boogu-Image-0.1-Base
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.
Nano Banana 2.1
- Subscription
- At Google from €4.99 a month (Google AI Plus, with limited credits). Through other providers from €6.83 a month (Poe Basic, with limited points). 42 plans in Germany.
- Via API
- No API price known. Access: API, Web app.
- Weights
- unknown.
Boogu-Image-0.1-Base
- 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 | Nano Banana 2.1 | Boogu-Image-0.1-Base |
|---|---|---|
| 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 | 10 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 72 | 9 |
| Product photographyMaterials, reflections, and fine details | 70 | 8 |
| Character and detailAnatomy, clothing, and spatial consistency | 57 | 8 |
| InfographicNumbers, labels, and visual organization | 64 | 16 |
| API price | ||
| Per imagelower is better | n/a | n/a |
| 100 images | n/a | n/a |
| Profile | ||
| Released | Oct 6, 2026 | n/a |
| Weightsopen means: runs locally | unknown | open |
| Access | API, Web app | local |
| Parameters | not published | 10 billion |
| Largest output | not consistently published | not consistently published |
| Plans in Germanynaming exactly this model | 42 | n/a |
API prices for one image at 1,024 × 1,024 pixels according to Artificial Analysis.
Sources: Nano Banana 2.1 model source (verified Nov 1, 2026) · Boogu-Image-0.1-Base 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 Nano Banana 2.1 and Boogu-Image-0.1-Base from the same arena and category. Older model versions are not used as substitutes.
More comparisons
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