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Qwen-Image-2.1vs.SDXL Turbo

Which one is better?

In our own test, Qwen-Image-2.1 leads. SDXL Turbo has no arena rating yet. Neither has an API price.

Test images

Same task, the first image of each. The task with the biggest difference is preselected.

Qwen-Image-2.1: Product photography, first image from the fixed test run
Qwen-Image-2.190 out of 100
SDXL Turbo: Product photography, first image from the fixed test run
SDXL Turbo3 out of 100

Result for “Product photography”:Qwen-Image-2.1 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.

Character and detail

Qwen-Image-2.1: manual, 1:1, requested and received 1024x1024, one request, first output, Qwen/Qwen-Image-2.1 base, 40 steps, true CFG 1.0, prompt enhancement disabled, no negative prompt, no reference images, seed=1591420783, official Space commit 5694809f4c56a4e8c40787b5392cecac36493c5d, generated Nov 1, 2026, 8:49 AM. 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

Qwen-Image-2.1 image SHA 256: b29bb7e207ad464957ee060bbf0655104bcbece703360254e48daa3ec35a62d7

SDXL Turbo image SHA 256: 9ee6443f4690649e93bdca408e5e8d317b312244636a3af47a02fe14eaf6c20c

Infographic

Qwen-Image-2.1: manual, 1:1, requested and received 1024x1024, one request, first output, Qwen/Qwen-Image-2.1 base, 40 steps, true CFG 1.0, prompt enhancement disabled, no negative prompt, no reference images, seed=1283422012, official Space commit 5694809f4c56a4e8c40787b5392cecac36493c5d, prior anonymous attempt refused before inference (ZeroGPU quota), completed through authenticated browser, generated Nov 1, 2026, 8:49 AM. 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=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

Qwen-Image-2.1 image SHA 256: 316e38ed63ff401f86a7ceee9cc65c74413e0e9c7c899a6e6bf453acc2940dac

SDXL Turbo image SHA 256: 20395d858252aa131f235baa1f514039503a52dfec958c8f5b299db708bf4090

Product photography

Qwen-Image-2.1: manual, 1:1, requested and received 1024x1024, one request, first output, Qwen/Qwen-Image-2.1 base, 40 steps, true CFG 1.0, prompt enhancement disabled, no negative prompt, no reference images, seed=196359631, official Space commit 5694809f4c56a4e8c40787b5392cecac36493c5d, generated Nov 1, 2026, 8:49 AM. 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=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

Qwen-Image-2.1 image SHA 256: 041f559d4261865b327fcae4f8bb0bd3b176c55a3b1255a042ab3e0fc4f9bc4b

SDXL Turbo image SHA 256: 75e5b85283110815e51a0470c937c3e42407244b50d918a3c0c54e10998a4b4c

Typography and layout

Qwen-Image-2.1: manual, 1:1, requested and received 1024x1024, one request, first output, Qwen/Qwen-Image-2.1 base, 40 steps, true CFG 1.0, prompt enhancement disabled, no negative prompt, no reference images, seed=158818011, official Space commit 5694809f4c56a4e8c40787b5392cecac36493c5d, generated Nov 1, 2026, 8:49 AM. 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=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

Qwen-Image-2.1 image SHA 256: 4670269190f492154c05e3f18c4eb9e3938910ca1aca32503b6a1ceb16d39b38

SDXL Turbo image SHA 256: 963088c72f75c98a95fd71be5f8d6e14fdf17061ae984f1109522a39be24ac76

The numbers at a glance

Arena ratingfrom votes by users · higher is better
1,227

Qwen-Image-2.1

Rank 14 of 21

n/a

SDXL Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better
65

Qwen-Image-2.1

Rank 40 of 108

4

SDXL Turbo

Rank 105 of 108

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

Qwen-Image-2.1

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.

Qwen-Image-2.1

Subscription
No Alibaba subscription includes this model. Through other providers from ≈ €9.54 a month (Krea Basic, with limited credits). 5 plans in Germany.
Via API
No API price known. Access: local, Web app.
License
Open weights, Qwen Research License: non-commercial use only; commercial use requires a separate license.

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.

Arena rating (LMArena) from Nov 6, 2026 · 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.

KennzahlQwen-Image-2.1SDXL Turbo
Ratings
Arena ratingfrom votes by users, higher is better1,227n/a
Arena rankRank 14 of 21n/a
Arena votesmore votes, a safer rating19,378n/a
GraduallyBenchour own rating, 0 to 100654
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition543
Product photographyMaterials, reflections, and fine details903
Character and detailAnatomy, clothing, and spatial consistency343
InfographicNumbers, labels, and visual organization838
API price
Per imagelower is bettern/an/a
100 imagesn/an/a
Profile
ReleasedSep 20, 2026n/a
Weightsopen means: runs locallyopenQwen Research License: non-commercial use only; commercial use requires a separate licenseopen
Lifecycleno noticeOlder open fast checkpoint; no active hosted API ID claimed in the reviewed model list
Accesslocal, Web applocal
Parametersnot publishednot published
Largest output2Knot consistently published
Plans in Germanynaming exactly this model5n/a

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

Sources: Qwen-Image-2.1 model source, status source (verified Sep 22, 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 Qwen-Image-2.1 and SDXL Turbo from the same arena and category. Older model versions are not used as substitutes.

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