SenseNova U1.5 Litevs.Z-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.

SenseNova U1.5 Lite: Product photography, first image from the fixed test run — SenseNova U1.5 Lite84 out of 100

Z-Image Turbo: Product photography, first image from the fixed test run — Z-Image Turbo30 out of 100

Result for “Product photography”:SenseNova U1.5 Lite 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

SenseNova U1.5 Lite: manual, local stable-diffusion.cpp@3be23788fc0c9f35a2c24b1211caae11d4a54dbc, ggml@d49c49e1dd361ba3c0a77c90b5b1404b83969aa8; sensenova/SenseNova-U1.5-8B-MoT@9feeeab8a2792514d109cd34589342a2cc1d4ab2; native 2048x2048, 1:1; one request, first output; steps=50, guidance=4.0, seed=8087247682796819534; Apple M5 Max Metal MTL0 requested through the native backend option; automatic placement remains enabled, and actual placement is recorded in the CLI log; Original BF16 checkpoint. The exact two SenseNova vision convolution weights use a targeted lossless BF16-to-F32 rule; other eligible weights use the native unquantized f16 option. This BF16-to-F16 conversion rounds values, as quantified by the linked complete-checkpoint GGML preflight; excluded weights remain BF16 if used. Operation precision follows the backend.; Euler, flow shift 3; CPU Philox RNG (CLI cuda RNG option, no CUDA hardware); original BF16 weights without requested quantization; observational latent and pre-clipping finite checks; native prompt template without rewriting; empty unconditional prompt, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 10:17 PM. Source

Z-Image Turbo: fal, requested 1024x1024, n=1, seed=457367499, prompt expansion disabled, estimated cost $0.010000, generated Nov 1, 2026, 9:35 PM. Source

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

SenseNova U1.5 Lite image SHA 256: c092b333f479c5b28ad33958d0e45f0fb0989970af02690079cf1398742c55b8

Z-Image Turbo image SHA 256: 5297796931ae8a9259947d2ee85881444a6408266aa7c9bc45d365b56bd11fe1

Infographic

SenseNova U1.5 Lite: manual, local stable-diffusion.cpp@3be23788fc0c9f35a2c24b1211caae11d4a54dbc, ggml@d49c49e1dd361ba3c0a77c90b5b1404b83969aa8; sensenova/SenseNova-U1.5-8B-MoT@9feeeab8a2792514d109cd34589342a2cc1d4ab2; native 2048x2048, 1:1; one request, first output; steps=50, guidance=4.0, seed=2640628636372692680; Apple M5 Max Metal MTL0 requested through the native backend option; automatic placement remains enabled, and actual placement is recorded in the CLI log; Original BF16 checkpoint. The exact two SenseNova vision convolution weights use a targeted lossless BF16-to-F32 rule; other eligible weights use the native unquantized f16 option. This BF16-to-F16 conversion rounds values, as quantified by the linked complete-checkpoint GGML preflight; excluded weights remain BF16 if used. Operation precision follows the backend.; Euler, flow shift 3; CPU Philox RNG (CLI cuda RNG option, no CUDA hardware); original BF16 weights without requested quantization; observational latent and pre-clipping finite checks; native prompt template without rewriting; empty unconditional prompt, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 10:25 PM. Source

Z-Image Turbo: fal, requested 1024x1024, n=1, seed=364147116, prompt expansion disabled, estimated cost $0.010000, generated Nov 1, 2026, 9:35 PM. Source

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

SenseNova U1.5 Lite image SHA 256: dcf8206386da05d11c35a6950309e61f08a504d440366226eac316328718f5ae

Z-Image Turbo image SHA 256: 2a0bbce06ee9f7e009876b2d9abc02657f7be5535cd79ab7f37df0bf61b141a8

Product photography

SenseNova U1.5 Lite: manual, local stable-diffusion.cpp@3be23788fc0c9f35a2c24b1211caae11d4a54dbc, ggml@d49c49e1dd361ba3c0a77c90b5b1404b83969aa8; sensenova/SenseNova-U1.5-8B-MoT@9feeeab8a2792514d109cd34589342a2cc1d4ab2; native 2048x2048, 1:1; one request, first output; steps=50, guidance=4.0, seed=1950293105094404455; Apple M5 Max Metal MTL0 requested through the native backend option; automatic placement remains enabled, and actual placement is recorded in the CLI log; Original BF16 checkpoint. The exact two SenseNova vision convolution weights use a targeted lossless BF16-to-F32 rule; other eligible weights use the native unquantized f16 option. This BF16-to-F16 conversion rounds values, as quantified by the linked complete-checkpoint GGML preflight; excluded weights remain BF16 if used. Operation precision follows the backend.; Euler, flow shift 3; CPU Philox RNG (CLI cuda RNG option, no CUDA hardware); original BF16 weights without requested quantization; observational latent and pre-clipping finite checks; native prompt template without rewriting; empty unconditional prompt, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 10:11 PM. Source

Z-Image Turbo: fal, requested 1024x1024, n=1, seed=453185405, prompt expansion disabled, estimated cost $0.010000, generated Nov 1, 2026, 9:35 PM. Source

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

SenseNova U1.5 Lite image SHA 256: d425ed5236325ee28633f83cb00f3fd39181f7dd6df0e5408d8b1c07c6796107

Z-Image Turbo image SHA 256: 16330b5b71c71290aaa2994dd589e5e2088712d286fddcee8046e56c300f124e

Typography and layout

SenseNova U1.5 Lite: manual, local stable-diffusion.cpp@3be23788fc0c9f35a2c24b1211caae11d4a54dbc, ggml@d49c49e1dd361ba3c0a77c90b5b1404b83969aa8; sensenova/SenseNova-U1.5-8B-MoT@9feeeab8a2792514d109cd34589342a2cc1d4ab2; native 2048x2048, 1:1; one request, first output; steps=50, guidance=4.0, seed=8328647217678382438; Apple M5 Max Metal MTL0 requested through the native backend option; automatic placement remains enabled, and actual placement is recorded in the CLI log; Original BF16 checkpoint. The exact two SenseNova vision convolution weights use a targeted lossless BF16-to-F32 rule; other eligible weights use the native unquantized f16 option. This BF16-to-F16 conversion rounds values, as quantified by the linked complete-checkpoint GGML preflight; excluded weights remain BF16 if used. Operation precision follows the backend.; Euler, flow shift 3; CPU Philox RNG (CLI cuda RNG option, no CUDA hardware); original BF16 weights without requested quantization; observational latent and pre-clipping finite checks; native prompt template without rewriting; empty unconditional prompt; three local execution attempts: original Metal BF16 attempt aborted on a missing matrix kernel before output; same-seed CPU retry deliberately interrupted before its first sampling step without image or latent; first image retained after the reviewed loader compatibility correction and disclosed F16 runtime conversion with unchanged prompt and seed, source 2048x2048, stored 1024x1024 (Lanczos3 downscale), generated Nov 2, 2026, 10:04 PM. Source

Z-Image Turbo: fal, requested 1024x1024, n=1, seed=249593273, prompt expansion disabled, estimated cost $0.010000, generated Nov 1, 2026, 9:35 PM. Source

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

SenseNova U1.5 Lite image SHA 256: df5c50fc54f03b972796f424999bd5991ff758a6b7abc00c212864aca3b124bc

Z-Image Turbo image SHA 256: 0a9ee8166b04fc677b96ca3f74d8fcf37657d812f81d3b94940092aa661dba50

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

SenseNova U1.5 Lite

not in the arena

n/a

Z-Image Turbo

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

SenseNova U1.5 Lite

Rank 14 of 108

Z-Image Turbo

Rank 67 of 108

Price per imagedollars through the API · lower is better

n/a

SenseNova U1.5 Lite

no API price

n/a

Z-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.

SenseNova U1.5 Lite

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

Z-Image Turbo

Subscription: No Tongyi-MAI / Alibaba subscription includes this model. Through other providers from ≈ €12.72 a month (Recraft Basic, with limited credits). 3 plans in Germany.
Via API: No API price known. Access: API, 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.

Kennzahl	SenseNova U1.5 Lite	Z-Image 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	73	44
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	93	40
Product photographyMaterials, reflections, and fine details	84	30
Character and detailAnatomy, clothing, and spatial consistency	35	71
InfographicNumbers, labels, and visual organization	80	37
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	n/a	Nov 26, 2025
Weightsopen means: runs locally	open	open
Access	API, Web app, local	API, local, Web app
Parameters	not published	not published
Largest output	4K	2K
Plans in Germanynaming exactly this model	n/a	3

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

Sources: SenseNova U1.5 Lite model source (verified Nov 2, 2026) · Z-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 SenseNova U1.5 Lite and Z-Image Turbo from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare SenseNova U1.5 Lite and Z-Image Turbo with the models people compare them with most often.

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