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Midjourney V8.1vs.LLaDA-Image-Turbo

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: Product photography, first image from the fixed test run
Midjourney V8.150 out of 100
LLaDA-Image-Turbo: Product photography, first image from the fixed test run
LLaDA-Image-Turbo27 out of 100

Result for “Product photography”:Midjourney V8.1 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.

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

LLaDA-Image-Turbo: manual, 1:1, native 1024x1024, one request in the successful technical repeat, first output; two total submissions after a local download failure; seed 0 (fixed provider default, randomize_seed=false); BF16 transformer, FP8 text encoder; 4 steps, CFG 1.0; HF Space commit 7b02431121944d65b8065873b48eec736a0c1022; source PNG SHA-256 d1866b4994a664728de07f1c1897776bbf04409b4a00ad7fa98666036a78816d, generated Nov 2, 2026, 3:03 PM. Source

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

Midjourney V8.1 image SHA 256: af3d2c5042b108a7fe2eb49bae072d30030e6b6cf814875ef9ce7074ceafc4ce

LLaDA-Image-Turbo image SHA 256: de0c780506575a32050ce9ca3d3c4dd1a0c4cc7ccf7f7f2f6aaf17ad01295901

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

LLaDA-Image-Turbo: manual, PyTorch 2.13.0, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image-Turbo@f4afc52d925bbac4e22a1c947111fc1f127e37e5; native 1024x1024, 1:1; one request per local attempt, first output; steps=4, guidance=1.0; seed=0; separate MPS initial-latent generator and global MPS scheduler RNG streams with the same integer seed; original Turbo scheduler, stochastic_sampling=true, uniform sigmas, shift=3; BF16 text encoder and diffusion components, FP32 denoising latent and CPU FP32 VAE decode; historical poster uses FP8 text encoder and remains unchanged; no CUDA equivalence claimed; MPS fallback permitted, actual fallback operations not measured; historical Hugging Face Space product-photo attempt used the same archived prompt and seed 0 but a different request body and backend; its AppError left the output unresolved; this is not an exact request replay or a numerical-equivalence comparison, generated Nov 3, 2026, 9:48 AM. Source

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

Midjourney V8.1 image SHA 256: 992f2486be40bc361a638b4b266909d334883c05fe4763cf5e243358c688bfdd

LLaDA-Image-Turbo image SHA 256: e61fb35e0c12941d28d32b0e0125b934bc0857fc49216a7945406e3bf58b4316

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

LLaDA-Image-Turbo: manual, PyTorch 2.13.0, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image-Turbo@f4afc52d925bbac4e22a1c947111fc1f127e37e5; native 1024x1024, 1:1; one request per local attempt, first output; steps=4, guidance=1.0; seed=7961710876241130415; separate MPS initial-latent generator and global MPS scheduler RNG streams with the same integer seed; original Turbo scheduler, stochastic_sampling=true, uniform sigmas, shift=3; BF16 text encoder and diffusion components, FP32 denoising latent and CPU FP32 VAE decode; historical poster uses FP8 text encoder and remains unchanged; no CUDA equivalence claimed; MPS fallback permitted, actual fallback operations not measured, generated Nov 3, 2026, 9:54 AM. Source

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

Midjourney V8.1 image SHA 256: cf522740817fefe58b263fa9a0d07d249c42211eca7d7c9b013f7145a7d2a8ea

LLaDA-Image-Turbo image SHA 256: aac02152ef0efc45749b3d0a626e9f4114418394aeb6a92d492651c564f40fee

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

LLaDA-Image-Turbo: manual, PyTorch 2.13.0, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image-Turbo@f4afc52d925bbac4e22a1c947111fc1f127e37e5; native 1024x1024, 1:1; one request per local attempt, first output; steps=4, guidance=1.0; seed=5156250474893981751; separate MPS initial-latent generator and global MPS scheduler RNG streams with the same integer seed; original Turbo scheduler, stochastic_sampling=true, uniform sigmas, shift=3; BF16 text encoder and diffusion components, FP32 denoising latent and CPU FP32 VAE decode; historical poster uses FP8 text encoder and remains unchanged; no CUDA equivalence claimed; MPS fallback permitted, actual fallback operations not measured, generated Nov 3, 2026, 9:56 AM. Source

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

Midjourney V8.1 image SHA 256: ac36188f88f37f23c2c405355d8dd12594085e1450d732fa419d8cec9a6c598f

LLaDA-Image-Turbo image SHA 256: 4e8939998310be86b1ad3dc0744a5e3ceee95a00a9113ee6732f9c06cb6b3618

The numbers at a glance

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

Midjourney V8.1

not in the arena

n/a

LLaDA-Image-Turbo

not in the arena

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

Midjourney V8.1

Rank 73 of 108

31

LLaDA-Image-Turbo

Rank 83 of 108

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

Midjourney V8.1

no API price

n/a

LLaDA-Image-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.

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.

LLaDA-Image-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.

KennzahlMidjourney V8.1LLaDA-Image-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 1003831
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition148
Product photographyMaterials, reflections, and fine details5027
Character and detailAnatomy, clothing, and spatial consistency5153
InfographicNumbers, labels, and visual organization3536
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
ReleasedApr 14, 2026Sep 4, 2026
Weightsopen means: runs locallyproprietaryopen
AccessWeb applocal
Parametersnot published6 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) · LLaDA-Image-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 Midjourney V8.1 and LLaDA-Image-Turbo from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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