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Krea 2 Medium Turbovs.Boogu-Image-0.1-Base

Which one is better?

In our own test, Krea 2 Medium Turbo leads. Neither is in the arena. 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.

Krea 2 Medium Turbo: Product photography, first image from the fixed test run
Krea 2 Medium Turbo81 out of 100
Boogu-Image-0.1-Base: Product photography, first image from the fixed test run
Boogu-Image-0.1-Base8 out of 100

Result for “Product photography”:Krea 2 Medium Turbo ahead

Prompt given to both modelsCreate a square premium product photograph of a brushed titanium wristwatch standing upright on dark green marble. The watch has a cream dial, thin black hands set to 10:10, twelve distinct hour markers, a realistic crown, and a dark brown leather strap. Soft window light from the left, controlled reflections, shallow depth of field, no text, no logo, no extra objects.

What the rating looks at: Materials, reflections, and fine details.

“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

Krea 2 Medium Turbo: openrouter, aspect ratio 1:1, resolution 1K, one request, first returned image, seed=provider random, actual cost $0.015000, generated Aug 14, 2026, 1:35 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

Krea 2 Medium Turbo image SHA 256: a51c5eeb5ba6b3ab8be3cb1d9c36fc196d71f4034ff7e57c695af1fe2f4ab078

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

Infographic

Krea 2 Medium Turbo: openrouter, aspect ratio 1:1, resolution 1K, one request, first returned image, seed=provider random, actual cost $0.015000, generated Aug 14, 2026, 1:35 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

Krea 2 Medium Turbo image SHA 256: 10398e0fce4a5b07b8a38a010eec70ac5457d0209ef67979feebb111d315fe16

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

Product photography

Krea 2 Medium Turbo: openrouter, aspect ratio 1:1, resolution 1K, one request, first returned image, seed=provider random, actual cost $0.015000, generated Aug 14, 2026, 1:35 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

Krea 2 Medium Turbo image SHA 256: e1511de7ba316289e69ae79e51b4f75c80ee1468611f4cebcfc9d21658b19cb8

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

Typography and layout

Krea 2 Medium Turbo: openrouter, aspect ratio 1:1, resolution 1K, one request, first returned image, seed=provider random, actual cost $0.015000, generated Aug 14, 2026, 2:05 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

Krea 2 Medium Turbo image SHA 256: 50b1b1bb7196a612240ab6088330985474c9f60ccaf640e4aa8debb0aa20e1c8

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

The numbers at a glance

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

Krea 2 Medium Turbo

not in the arena

n/a

Boogu-Image-0.1-Base

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
65

Krea 2 Medium Turbo

Rank 39 of 108

10

Boogu-Image-0.1-Base

Rank 103 of 108

Price per imagedollars through the API · lower is better
$0.015

Krea 2 Medium Turbo

cheap

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.

Krea 2 Medium Turbo

Subscription
Free to use at Krea (Krea Free, with limited credits), more from ≈ €9.54 a month (Krea Basic, with limited credits). Through other providers from ≈ €12.72 a month (Leonardo.Ai Essential). 15 plans in Germany.
Via API
$0.015 per image, 100 images $1.50.

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 · 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.

KennzahlKrea 2 Medium TurboBoogu-Image-0.1-Base
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 1006510
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition719
Product photographyMaterials, reflections, and fine details818
Character and detailAnatomy, clothing, and spatial consistency308
InfographicNumbers, labels, and visual organization7916
API price
Per imagelower is better$0.015n/a
100 images$1.50n/a
Profile
ReleasedJune 2026n/a
Weightsopen means: runs locallyproprietaryopen
AccessAPI, Web applocal
Parametersnot published10 billion
Largest output1Knot consistently published
Plans in Germanynaming exactly this model15n/a

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

Sources: Krea 2 Medium Turbo model 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 Krea 2 Medium Turbo 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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