GPT Image 2.5 Flarevs.Boogu-Image-0.1-Base
Which one is better?
In our own test, GPT Image 2.5 Flare 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.
Result for “Infographic”:GPT Image 2.5 Flare ahead
What the rating looks at: Numbers, labels, and visual organization.
“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
GPT Image 2.5 Flare: openai, 1024x1024, quality high, n=1, generated Sep 28, 2026, 8:53 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
GPT Image 2.5 Flare image SHA 256: 85b17c41b19389cae3ea073ef582e6065a321d741978e772987d22e3ea3e3b08
Boogu-Image-0.1-Base image SHA 256: 5ca2782a121b2ffdd620953a4453df06769a5d51778c7980e1cddc8b8e79e0dd
Infographic
GPT Image 2.5 Flare: openai, 1024x1024, quality high, n=1, generated Sep 28, 2026, 8:53 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
GPT Image 2.5 Flare image SHA 256: bc752abfce1c0d27b73e4084c3e7d82c4c0f71e0e5af97a80f4b24326cc4686e
Boogu-Image-0.1-Base image SHA 256: 7b4a49a08dcb03776edaf18345ffe94ee7ae0293be8b3611bf676aa6c76c6405
Product photography
GPT Image 2.5 Flare: openai, 1024x1024, quality high, n=1, generated Sep 28, 2026, 8:53 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
GPT Image 2.5 Flare image SHA 256: 69fedb7d635d1329c461ff1ee9e5cf8384119e218e3b3bdb93b9e11f728335d8
Boogu-Image-0.1-Base image SHA 256: d0e66f73a26844f514cb97bbbd69bb8f4bf39bd875ac8fca0f04989949a64478
Typography and layout
GPT Image 2.5 Flare: openai, 1024x1024, quality high, n=1, generated Sep 28, 2026, 8:52 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
GPT Image 2.5 Flare image SHA 256: cc90d54a99e1bad9e0cc8e4196746fb1d56a2fdd2a9ee101dbbf270ef5e4b6a8
Boogu-Image-0.1-Base image SHA 256: b9abc77788966e5c8425e7a94c12632b4e4ec11e6d41c7afd0e1acdc37602db3
The numbers at a glance
GPT Image 2.5 Flare
Rank 2 of 21
Boogu-Image-0.1-Base
not in the arena
GPT Image 2.5 Flare
Rank 18 of 108
Boogu-Image-0.1-Base
Rank 103 of 108
GPT Image 2.5 Flare
expensive
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.
GPT Image 2.5 Flare
- Subscription
- No OpenAI subscription includes this model. Through other providers from ≈ €6.36 a month (ElevenLabs Starter, with limited credits). 61 plans in Germany.
- Via API
- $0.21 per image, 100 images $21.07.
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 | GPT Image 2.5 Flare | Boogu-Image-0.1-Base |
|---|---|---|
| Ratings | ||
| Arena ratingfrom votes by users, higher is better | 1,399 | n/a |
| Arena rank | Rank 2 of 21 | n/a |
| Arena votesmore votes, a safer rating | 53,925 | n/a |
| GraduallyBenchour own rating, 0 to 100 | 72 | 10 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 64 | 9 |
| Product photographyMaterials, reflections, and fine details | 69 | 8 |
| Character and detailAnatomy, clothing, and spatial consistency | 63 | 8 |
| InfographicNumbers, labels, and visual organization | 91 | 16 |
| API price | ||
| Per imagelower is better | $0.21 | n/a |
| 100 images | $21.07 | n/a |
| Profile | ||
| Released | Sep 8, 2026 | n/a |
| Weightsopen means: runs locally | proprietary | open |
| Access | API | local |
| Parameters | not published | 10 billion |
| Largest output | not consistently published | not consistently published |
| Plans in Germanynaming exactly this model | 61 | n/a |
API prices for one image at 1,024 × 1,024 pixels according to Artificial Analysis.
Sources: GPT Image 2.5 Flare model source (verified Sep 22, 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 GPT Image 2.5 Flare and Boogu-Image-0.1-Base from the same arena and category. Older model versions are not used as substitutes.
More comparisons
Compare GPT Image 2.5 Flare and Boogu-Image-0.1-Base with the models people compare them with most often.