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FLUX1.1 [pro] Ultravs.Boogu-Image-0.1-Turbo

Which one is better?

In our own test, FLUX1.1 [pro] Ultra 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.

FLUX1.1 [pro] Ultra: Character and detail, first image from the fixed test run
FLUX1.1 [pro] Ultra45 out of 100
Boogu-Image-0.1-Turbo: Character and detail, first image from the fixed test run
Boogu-Image-0.1-Turbo5 out of 100

Result for “Character and detail”:FLUX1.1 [pro] Ultra 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

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=3831910390, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 PM. Source

Boogu-Image-0.1-Turbo: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Turbo@47cd26d3c211b030c64ffe60d63b2e17a7c519c2; native 1024x1024, 1:1; one request, first output; steps=4, guidance=1.0, seed=2111621457284287488; 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 DMD student inference, conditioning sigma 0.001, generated Nov 2, 2026, 11:24 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 0b97e1e3f33be2844c06cc18618fea633273ada7e9d6404f9769cdb8403ffbfc

Boogu-Image-0.1-Turbo image SHA 256: 0c90d3a3e12870784d8b576ac3ace689b6cb627a4222f7cfc4a0d3793b9e4a37

Infographic

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=1664027293, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:50 PM. Source

Boogu-Image-0.1-Turbo: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Turbo@47cd26d3c211b030c64ffe60d63b2e17a7c519c2; native 1024x1024, 1:1; one request, first output; steps=4, guidance=1.0, seed=8524023330556932596; 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 DMD student inference, conditioning sigma 0.001, generated Nov 2, 2026, 11:24 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 2c7d24fcda220cf5eff966e1b857f11ad0e561f81ac9e4106ef1b4bd71686637

Boogu-Image-0.1-Turbo image SHA 256: 096ae82e5a28ef1095f159019c41983c84a0c670a76e752fb3a1f9600fa7c45a

Product photography

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=291934417, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:49 PM. Source

Boogu-Image-0.1-Turbo: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Turbo@47cd26d3c211b030c64ffe60d63b2e17a7c519c2; native 1024x1024, 1:1; one request, first output; steps=4, guidance=1.0, seed=9219148100655939974; 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 DMD student inference, conditioning sigma 0.001, generated Nov 2, 2026, 11:23 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 7d497c35126a92de69af61e5721158a10f4e2acf88a8526dcdd0f8a9a571e028

Boogu-Image-0.1-Turbo image SHA 256: 50719aadf378d21848c83dbdb510a8134c80be05cbb2b718182a95e9cbb28164

Typography and layout

FLUX1.1 [pro] Ultra: fal, aspect ratio 1:1; provider-native resolution, n=1, seed=1909595532, Fal exposes no resolution input; endpoint supports output up to 2K, Prompt enhancement disabled with enhance_prompt=false; default safety tolerance 2, estimated cost $0.060000, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 2:49 PM. Source

Boogu-Image-0.1-Turbo: manual, local PyTorch 2.11.0, Diffusers 0.38.0; Boogu/Boogu-Image-0.1-Turbo@47cd26d3c211b030c64ffe60d63b2e17a7c519c2; native 1024x1024, 1:1; one request, first output; steps=4, guidance=1.0, seed=4970356096182813142; 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 DMD student inference, conditioning sigma 0.001; two local attempts: original MPSGraph SIGABRT before output; one identical-prompt, identical-seed technical repeat after reviewed backend-only correction, first output retained; exact failing original operator is not proven, generated Nov 2, 2026, 11:18 PM. Source

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

FLUX1.1 [pro] Ultra image SHA 256: 0dfeffb6c3489b9ac2e1ae9100793320fa4f5eab779269de7aff3a4b768595f3

Boogu-Image-0.1-Turbo image SHA 256: cec0e99f796e6d0e4dafc517afc93fd93041aecbd52cef74a421ea9c3a15ab69

The numbers at a glance

Arena ratingfrom votes by users · higher is better
n/a

FLUX1.1 [pro] Ultra

not in the arena

n/a

Boogu-Image-0.1-Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
31

FLUX1.1 [pro] Ultra

Rank 83 of 108

9

Boogu-Image-0.1-Turbo

Rank 104 of 108

Price per imagedollars through the API · lower is better
n/a

FLUX1.1 [pro] Ultra

no API price

n/a

Boogu-Image-0.1-Turbo

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.

FLUX1.1 [pro] Ultra

Subscription
No Black Forest Labs subscription includes this model. Through other providers from ≈ €9.54 a month (Krea Basic, with limited credits). 12 plans in Germany.
Via API
No API price known. Access: API.
Weights
unknown.

Boogu-Image-0.1-Turbo

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.

KennzahlFLUX1.1 [pro] UltraBoogu-Image-0.1-Turbo
Ratings
Arena ratingfrom votes by users, higher is bettern/an/a
Arena rankn/an/a
Arena votesmore votes, a safer ratingn/an/a
GraduallyBenchour own rating, 0 to 100319
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition2218
Product photographyMaterials, reflections, and fine details286
Character and detailAnatomy, clothing, and spatial consistency455
InfographicNumbers, labels, and visual organization288
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
Releasedn/an/a
Weightsopen means: runs locallyunknownopen
LifecycleSeparate Ultra API route / Ultra mode; no independent checkpoint establishedno notice
AccessAPIlocal
Parametersnot published10 billion
Largest outputnot consistently publishednot consistently published
Plans in Germanynaming exactly this model12n/a

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

Sources: FLUX1.1 [pro] Ultra model source, status source (verified Nov 1, 2026) · Boogu-Image-0.1-Turbo 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 FLUX1.1 [pro] Ultra and Boogu-Image-0.1-Turbo from the same arena and category. Older model versions are not used as substitutes.

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