Nano Banana 2vs.Boogu-Image-0.1-Base

Which one is better?

In our own test, Nano Banana 2 leads. Boogu-Image-0.1-Base has no arena rating yet. Boogu-Image-0.1-Base has no API price.

Test images

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

Nano Banana 2: Typography and layout, first image from the fixed test run — Nano Banana 2100 out of 100

Boogu-Image-0.1-Base: Typography and layout, first image from the fixed test run — Boogu-Image-0.1-Base9 out of 100

Result for “Typography and layout”:Nano Banana 2 ahead

Prompt given to both modelsCreate a square editorial poster for an imaginary night train called MONDFALTER. Show the exact German headline MONDFALTER and the exact subline BERLIN NACH LISSABON. Use a restrained midnight-blue and warm-cream palette, one stylized moth, strong Swiss-grid typography, generous negative space, and no additional words or logos.

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: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:15 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 image SHA 256: 5d3a70ed3fe3328484725565d9c91fb25fc7f745bd66872dae432444493a83de

Boogu-Image-0.1-Base image SHA 256: 5ca2782a121b2ffdd620953a4453df06769a5d51778c7980e1cddc8b8e79e0dd

Infographic

Nano Banana 2: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:15 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 image SHA 256: 66123dd4e8cd5d22ecdca9cca8e4c5853a8046370aa4861ffee807a8c122c769

Boogu-Image-0.1-Base image SHA 256: 7b4a49a08dcb03776edaf18345ffe94ee7ae0293be8b3611bf676aa6c76c6405

Product photography

Nano Banana 2: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 12:15 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 image SHA 256: 509871921c450f6f07ec28f91a380992db1b3017108fd5928fe0aa9670a1ecdc

Boogu-Image-0.1-Base image SHA 256: d0e66f73a26844f514cb97bbbd69bb8f4bf39bd875ac8fca0f04989949a64478

Typography and layout

Nano Banana 2: together, 1024x1024, n=1, seed=provider random, provider default steps, generated Aug 14, 2026, 1:59 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 image SHA 256: 06ae79c07d1604d3da3bbfa80bac73ac15c88af5cb8c013faaf5c9ea93092305

Boogu-Image-0.1-Base image SHA 256: b9abc77788966e5c8425e7a94c12632b4e4ec11e6d41c7afd0e1acdc37602db3

The numbers at a glance

Arena ratingfrom votes by users · higher is better

1,257

Nano Banana 2

Rank 8 of 21

n/a

Boogu-Image-0.1-Base

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Nano Banana 2

Rank 51 of 108

Boogu-Image-0.1-Base

Rank 103 of 108

Price per imagedollars through the API · lower is better

$0.067

Nano Banana 2

fairly expensive

n/a

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

Subscription: Free to use at Google (Google AI Free, with limited credits), more from €4.99 a month (Google AI Plus, with limited credits). Through other providers from ≈ €6.36 a month (ElevenLabs Starter, with limited credits). 73 plans in Germany.
Via API: $0.067 per image, 100 images $6.70.

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.

Arena rating (LMArena) from Nov 6, 2026 · GraduallyBench from Nov 3, 2026 · API prices from Nov 6, 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	Boogu-Image-0.1-Base
Ratings
Arena ratingfrom votes by users, higher is better	1,257	n/a
Arena rank	Rank 8 of 21	n/a
Arena votesmore votes, a safer rating	77,495	n/a
GraduallyBenchour own rating, 0 to 100	61	10
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	100	9
Product photographyMaterials, reflections, and fine details	45	8
Character and detailAnatomy, clothing, and spatial consistency	36	8
InfographicNumbers, labels, and visual organization	63	16
API price
Per imagelower is better	$0.067	n/a
100 images	$6.70	n/a
Profile
Released	February 2026	n/a
Weightsopen means: runs locally	proprietary	open
Lifecycle	Previous generation to Nano Banana 2.1; Google recommends Nano Banana 2.1 for all new projects, the stable API has existed since May 28, 2026 and no shutdown is announced, the arena entry names the earlier pre-release configuration	no notice
Access	API, Web app	local
Parameters	not published	10 billion
Largest output	4K	not consistently published
Plans in Germanynaming exactly this model	73	n/a

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

Sources: Nano Banana 2 model source, status source (verified Aug 15, 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 and Boogu-Image-0.1-Base from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare Nano Banana 2 and Boogu-Image-0.1-Base with the models people compare them with most often.

Nano Banana 2vs.Boogu-Image-0.1-Base

Test images

The numbers at a glance

Nano Banana 2

Boogu-Image-0.1-Base

All data side by side

Arena ratings by category

No shared arena score in the stored snapshot

More comparisons

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Predecessor and successor

The most popular comparisons