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Midjourney V8.1vs.MOSS-Image-Base

Which one is better?

In our own test both are on par. 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.

Midjourney V8.1: Typography and layout, first image from the fixed test run
Midjourney V8.114 out of 100
MOSS-Image-Base: Typography and layout, first image from the fixed test run
MOSS-Image-Base51 out of 100

Result for “Typography and layout”:MOSS-Image-Base 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

Midjourney V8.1: manual, one request, first output, Midjourney V8.1 Standard, 1:1, 1024x1024, four candidates, stylize 100, weird 0, variety 0, Raw off, personalization off, Relax mode, no reference image, no negative prompt, generated Aug 16, 2026, 12:19 PM. Source

MOSS-Image-Base: manual, local PyTorch 2.13.0, Diffusers 0.41.0; OpenMOSS-Team/MOSS-Image-Base@85975793d8b3d432f1b6e27f352abaa4c2a4c0d3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.0, seed=921965437095743280; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; unconditional skip layers=[22]; CPU operator fallback permitted, actual fallback use was not measured; official experimental MPS compatibility runtime OpenMOSS/MOSS-Image@1961ca3d111b828e65278656cde0c8f94484f4dd, generated Nov 2, 2026, 10:39 PM. Source

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

Midjourney V8.1 image SHA 256: cf522740817fefe58b263fa9a0d07d249c42211eca7d7c9b013f7145a7d2a8ea

MOSS-Image-Base image SHA 256: 313d95f3e7766e861d46b0563c81bb2a02782708004c24c7aab0c46e8587ff83

Infographic

Midjourney V8.1: manual, one request, first output, Midjourney V8.1 Standard, 1:1, 1024x1024, four candidates, stylize 100, weird 0, variety 0, Raw off, personalization off, Relax mode, no reference image, no negative prompt, generated Aug 16, 2026, 12:19 PM. Source

MOSS-Image-Base: manual, local PyTorch 2.13.0, Diffusers 0.41.0; OpenMOSS-Team/MOSS-Image-Base@85975793d8b3d432f1b6e27f352abaa4c2a4c0d3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.0, seed=2567672344276262662; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; unconditional skip layers=[22]; CPU operator fallback permitted, actual fallback use was not measured; official experimental MPS compatibility runtime OpenMOSS/MOSS-Image@1961ca3d111b828e65278656cde0c8f94484f4dd, generated Nov 2, 2026, 10:43 PM. Source

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

Midjourney V8.1 image SHA 256: ac36188f88f37f23c2c405355d8dd12594085e1450d732fa419d8cec9a6c598f

MOSS-Image-Base image SHA 256: 3175582007cf377490ab51f73a57ebddb312f523ac5bfb54ae7598e72eb3edca

Product photography

Midjourney V8.1: manual, one request, first output, Midjourney V8.1 Standard, 1:1, 1024x1024, four candidates, stylize 100, weird 0, variety 0, Raw off, personalization off, Relax mode, no reference image, no negative prompt, generated Aug 16, 2026, 12:19 PM. Source

MOSS-Image-Base: manual, local PyTorch 2.13.0, Diffusers 0.41.0; OpenMOSS-Team/MOSS-Image-Base@85975793d8b3d432f1b6e27f352abaa4c2a4c0d3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.0, seed=8912274556852986311; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; unconditional skip layers=[22]; CPU operator fallback permitted, actual fallback use was not measured; official experimental MPS compatibility runtime OpenMOSS/MOSS-Image@1961ca3d111b828e65278656cde0c8f94484f4dd, generated Nov 2, 2026, 10:35 PM. Source

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

Midjourney V8.1 image SHA 256: 992f2486be40bc361a638b4b266909d334883c05fe4763cf5e243358c688bfdd

MOSS-Image-Base image SHA 256: af9ea47eb1554bcaaaadf8860fecfa5bb69095a58bf346e3d9a73be8240a2a7c

Typography and layout

Midjourney V8.1: manual, one request, first output, Midjourney V8.1 Standard, 1:1, 1024x1024, four candidates, stylize 100, weird 0, variety 0, Raw off, personalization off, Relax mode, no reference image, no negative prompt, generated Aug 16, 2026, 12:19 PM. Source

MOSS-Image-Base: manual, local PyTorch 2.13.0, Diffusers 0.41.0; OpenMOSS-Team/MOSS-Image-Base@85975793d8b3d432f1b6e27f352abaa4c2a4c0d3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.0, seed=9219943416610765538; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; unconditional skip layers=[22]; CPU operator fallback permitted, actual fallback use was not measured; official experimental MPS compatibility runtime OpenMOSS/MOSS-Image@1961ca3d111b828e65278656cde0c8f94484f4dd, generated Nov 2, 2026, 10:31 PM. Source

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

Midjourney V8.1 image SHA 256: af3d2c5042b108a7fe2eb49bae072d30030e6b6cf814875ef9ce7074ceafc4ce

MOSS-Image-Base image SHA 256: e87b1d9d7aa09487c6b9be505746dacb2f3be551f29a5d85424a44a2a88089c5

The numbers at a glance

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

Midjourney V8.1

not in the arena

n/a

MOSS-Image-Base

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
38

Midjourney V8.1

Rank 73 of 108

51

MOSS-Image-Base

Rank 61 of 108

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

Midjourney V8.1

no API price

n/a

MOSS-Image-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.

Midjourney V8.1

Subscription
At Midjourney from ≈ €10.60 a month (Midjourney Basic). 4 plans in Germany.
Via API
No API price known. Access: Web app.

MOSS-Image-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.

KennzahlMidjourney V8.1MOSS-Image-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 1003851
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition1451
Product photographyMaterials, reflections, and fine details5036
Character and detailAnatomy, clothing, and spatial consistency5146
InfographicNumbers, labels, and visual organization3571
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
ReleasedApr 14, 2026Oct 16, 2026
Weightsopen means: runs locallyproprietaryopen
AccessWeb applocal
Parametersnot published5 billion
Largest output2Knot consistently published
Plans in Germanynaming exactly this model4n/a

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

Sources: Midjourney V8.1 model source (verified Aug 15, 2026) · MOSS-Image-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 Midjourney V8.1 and MOSS-Image-Base from the same arena and category. Older model versions are not used as substitutes.

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