LongCat-Imagevs.Boogu-Image-0.1-Base

Which one is better?

In our own test, LongCat-Image 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.

LongCat-Image: Typography and layout, first image from the fixed test run — LongCat-Image41 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”:LongCat-Image 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

LongCat-Image: fal, image_size=square_hd; exact native pixels are not request-configurable, n=1, seed=1234871882, Estimate reserves 2 MP at Fal's $0.13 per MP rate, estimated cost $0.260000, generated Nov 2, 2026, 3:06 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

LongCat-Image image SHA 256: 7c2d3cbf8efa756277fc1e20af0c0c7c4febec50b30244eb9b85c02c236e97ca

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

Infographic

LongCat-Image: fal, image_size=square_hd; exact native pixels are not request-configurable, n=1, seed=886012823, Estimate reserves 2 MP at Fal's $0.13 per MP rate, estimated cost $0.260000, generated Nov 2, 2026, 3:06 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

LongCat-Image image SHA 256: ce6df19ed744009c81aec8257cef3e5a4de7ea0d4985c709335ec1b50c3381fb

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

Product photography

LongCat-Image: fal, image_size=square_hd; exact native pixels are not request-configurable, n=1, seed=1319752608, Estimate reserves 2 MP at Fal's $0.13 per MP rate, estimated cost $0.260000, generated Nov 2, 2026, 3:06 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

LongCat-Image image SHA 256: 1f95d4152dfa60c5056df13bf813563a75863f4a34419344e1a59a800a46f689

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

Typography and layout

LongCat-Image: fal, image_size=square_hd; exact native pixels are not request-configurable, n=1, seed=943200407, Estimate reserves 2 MP at Fal's $0.13 per MP rate, estimated cost $0.260000, generated Nov 2, 2026, 3:06 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

LongCat-Image image SHA 256: 1d6b72ae389c339ff3011ee3c59bd77b12b5157f1fadcf0932c96ebe5313836b

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

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

LongCat-Image

not in the arena

n/a

Boogu-Image-0.1-Base

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

LongCat-Image

Rank 80 of 108

Boogu-Image-0.1-Base

Rank 103 of 108

Price per imagedollars through the API · lower is better

n/a

LongCat-Image

no API price

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.

LongCat-Image

Subscription: n/a No plan in Germany names exactly this model.
Via API: No API price known. Access: local.
License: Open weights.

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	LongCat-Image	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	33	10
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	41	9
Product photographyMaterials, reflections, and fine details	29	8
Character and detailAnatomy, clothing, and spatial consistency	24	8
InfographicNumbers, labels, and visual organization	37	16
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	Dec 5, 2025	n/a
Weightsopen means: runs locally	open	open
Access	local	local
Parameters	6 billion	10 billion
Largest output	not consistently published	not consistently published
Plans in Germanynaming exactly this model	n/a	n/a

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

Sources: LongCat-Image 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 LongCat-Image and Boogu-Image-0.1-Base from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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

Compare another matchup

First image modelSecond image model