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Wan 2.7 Image Provs.BAGEL-7B-MoT

Which one is better?

In our own test, Wan 2.7 Image Pro 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.

Wan 2.7 Image Pro: Infographic, first image from the fixed test run
Wan 2.7 Image Pro89 out of 100
BAGEL-7B-MoT: Infographic, first image from the fixed test run
BAGEL-7B-MoT6 out of 100

Result for “Infographic”:Wan 2.7 Image Pro ahead

Prompt given to both modelsCreate a square German infographic titled SO FUNKTIONIERT PHOTOSYNTHESE. Show exactly four numbered steps in this order: 1 LICHT, 2 WASSER, 3 CO₂, 4 ZUCKER + SAUERSTOFF. Use a clean editorial science style with one plant cross-section, simple arrows, high contrast, legible labels, and no other text.

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

Wan 2.7 Image Pro: fal, requested 1024x1024, n=1, seed=1941203496, estimated cost $0.075000, generated Nov 1, 2026, 9:25 PM. Source

BAGEL-7B-MoT: fal, provider-default image size; one output sampled; use_thought=false, one request, first output, seed=1668381318, Fal schema does not expose image size or image count fields, estimated cost $0.100000, generated Nov 2, 2026, 3:22 PM. Source

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

Wan 2.7 Image Pro image SHA 256: 0bd2cf4922b58d78d0e6ec3d804aaccd427e5317066816fdc039ca5c80f4de28

BAGEL-7B-MoT image SHA 256: f9a99e0e983d8731377afdf880911fc993d516b55c18059fd5cb3390fd01fd31

Infographic

Wan 2.7 Image Pro: fal, requested 1024x1024, n=1, seed=1839059937, estimated cost $0.075000, generated Nov 1, 2026, 9:26 PM. Source

BAGEL-7B-MoT: fal, provider-default image size; one output sampled; use_thought=false, one request, first output, seed=1401806471, Fal schema does not expose image size or image count fields, estimated cost $0.100000, generated Nov 2, 2026, 3:23 PM. Source

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

Wan 2.7 Image Pro image SHA 256: caa6b4e95e0676d9867358db906f1f029dd320960e9dd1b8300283a5e2723077

BAGEL-7B-MoT image SHA 256: fd19fd4a68dfc264705c92209fcf45e3c8be4384c02433888b066683ee57c2ba

Product photography

Wan 2.7 Image Pro: fal, requested 1024x1024, n=1, seed=1277346407, estimated cost $0.075000, generated Nov 1, 2026, 9:24 PM. Source

BAGEL-7B-MoT: fal, provider-default image size; one output sampled; use_thought=false, one request, first output, seed=1385391411, Fal schema does not expose image size or image count fields, estimated cost $0.100000, generated Nov 2, 2026, 3:22 PM. Source

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

Wan 2.7 Image Pro image SHA 256: 1ed875886c86963322fdf329bf809943b96886fb4f373197e1654256316ac67c

BAGEL-7B-MoT image SHA 256: e8ef4e099fe8329b2bba090a2b8fee5cf926dfc5f91ad8e8694b4a4c78ab8455

Typography and layout

Wan 2.7 Image Pro: fal, requested 1024x1024, n=1, seed=1291974856, estimated cost $0.075000, generated Nov 1, 2026, 9:23 PM. Source

BAGEL-7B-MoT: fal, provider-default image size; one output sampled; use_thought=false, one request, first output, seed=425487007, Fal schema does not expose image size or image count fields, estimated cost $0.100000, generated Nov 2, 2026, 3:21 PM. Source

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

Wan 2.7 Image Pro image SHA 256: 4e860e01ecb53ed47d9a3ad2be57e9f2567e8dc010e44780615f71e30713f648

BAGEL-7B-MoT image SHA 256: 401dd23a2e6578a4e676d10543a9fea92d94d0f535dee90d6c7a25e56143257a

The numbers at a glance

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

Wan 2.7 Image Pro

not in the arena

n/a

BAGEL-7B-MoT

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
84

Wan 2.7 Image Pro

Rank 1 of 108

34

BAGEL-7B-MoT

Rank 76 of 108

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

Wan 2.7 Image Pro

no API price

n/a

BAGEL-7B-MoT

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.

Wan 2.7 Image Pro

Subscription
At Alibaba from ≈ €6.36 a month (Token Plan Individual Lite, with limited credits). 7 plans in Germany.
Via API
No API price known. Access: API.
Weights
unknown.

BAGEL-7B-MoT

Subscription
n/a No plan in Germany names exactly this model.
Via API
No API price known. Access: local, Web app.
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.

KennzahlWan 2.7 Image ProBAGEL-7B-MoT
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 1008434
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition8111
Product photographyMaterials, reflections, and fine details8788
Character and detailAnatomy, clothing, and spatial consistency7832
InfographicNumbers, labels, and visual organization896
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
Releasedn/aMay 20, 2025
Weightsopen means: runs locallyunknownopen
AccessAPIlocal, Web app
Parametersnot published14 billion
Largest output4Knot consistently published
Plans in Germanynaming exactly this model7n/a

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

Sources: Wan 2.7 Image Pro model source (verified Nov 1, 2026) · BAGEL-7B-MoT 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 Wan 2.7 Image Pro and BAGEL-7B-MoT from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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