Midjourney V8.1vs.SDXL Turbo

Which one is better?

In our own test, Midjourney V8.1 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.

Midjourney V8.1: Character and detail, first image from the fixed test run — Midjourney V8.151 out of 100

SDXL Turbo: Character and detail, first image from the fixed test run — SDXL Turbo3 out of 100

Result for “Character and detail”:Midjourney V8.1 ahead

Prompt given to both modelsCreate a square cinematic full-body portrait of a fictional bicycle courier waiting under a transparent umbrella at a rainy tram stop in Hamburg at blue hour. She wears a mustard raincoat, navy trousers, red sneakers, a silver helmet, and carries a teal messenger bag. Keep both hands visible, render the bicycle correctly, use realistic wet-street reflections, and include no readable brand names.

What the rating looks at: Anatomy, clothing, and spatial consistency.

“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

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=660064698563452219; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:23 PM. Source

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

Midjourney V8.1 image SHA 256: cf522740817fefe58b263fa9a0d07d249c42211eca7d7c9b013f7145a7d2a8ea

SDXL Turbo image SHA 256: 9ee6443f4690649e93bdca408e5e8d317b312244636a3af47a02fe14eaf6c20c

Infographic

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=6060807684445796734; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:23 PM. Source

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

Midjourney V8.1 image SHA 256: ac36188f88f37f23c2c405355d8dd12594085e1450d732fa419d8cec9a6c598f

SDXL Turbo image SHA 256: 20395d858252aa131f235baa1f514039503a52dfec958c8f5b299db708bf4090

Product photography

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=4654331835179858246; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE; native tokenizer truncation: tokenizer 80 to 77 tokens, tokenizer_2 80 to 77 tokens; archived input unchanged, generated Nov 2, 2026, 6:22 PM. Source

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

Midjourney V8.1 image SHA 256: 992f2486be40bc361a638b4b266909d334883c05fe4763cf5e243358c688bfdd

SDXL Turbo image SHA 256: 75e5b85283110815e51a0470c937c3e42407244b50d918a3c0c54e10998a4b4c

Typography and layout

SDXL Turbo: manual, local PyTorch 2.13.0, Diffusers 0.36.0; stabilityai/sdxl-turbo@71153311d3dbb46851df1931d3ca6e939de83304; native 1024x1024, 1:1; one request, first output; steps=1, guidance=0.0, seed=1511362670078321145; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:21 PM. Source

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

Midjourney V8.1 image SHA 256: af3d2c5042b108a7fe2eb49bae072d30030e6b6cf814875ef9ce7074ceafc4ce

SDXL Turbo image SHA 256: 963088c72f75c98a95fd71be5f8d6e14fdf17061ae984f1109522a39be24ac76

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Midjourney V8.1

not in the arena

n/a

SDXL Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Midjourney V8.1

Rank 73 of 108

SDXL Turbo

Rank 105 of 108

Price per imagedollars through the API · lower is better

n/a

Midjourney V8.1

no API price

n/a

SDXL 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.

SDXL 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.

Kennzahl	Midjourney V8.1	SDXL Turbo
Ratings
Arena ratingfrom votes by users, higher is better	n/a	n/a
Arena rank	n/a	n/a
Arena votesmore votes, a safer rating	n/a	n/a
GraduallyBenchour own rating, 0 to 100	38	4
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	14	3
Product photographyMaterials, reflections, and fine details	50	3
Character and detailAnatomy, clothing, and spatial consistency	51	3
InfographicNumbers, labels, and visual organization	35	8
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	Apr 14, 2026	n/a
Weightsopen means: runs locally	proprietary	open
Lifecycle	no notice	Older open fast checkpoint; no active hosted API ID claimed in the reviewed model list
Access	Web app	local
Parameters	not published	not published
Largest output	2K	not consistently published
Plans in Germanynaming exactly this model	4	n/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) · SDXL Turbo model source, status 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 SDXL Turbo from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare Midjourney V8.1 and SDXL Turbo with the models people compare them with most often.

Midjourney V8.1vs.SDXL Turbo

Test images

The numbers at a glance

Midjourney V8.1

SDXL Turbo

All data side by side

Arena ratings by category

No shared arena score in the stored snapshot

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