Stable Diffusion 3.5 Largevs.SenseNova U1.5 Lite
Which one is better?
In our own test, SenseNova U1.5 Lite leads. SenseNova U1.5 Lite 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.
Result for “Product photography”:SenseNova U1.5 Lite ahead
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
Stable Diffusion 3.5 Large: fal, requested 1024x1024, n=1, seed=7087247023770270000, estimated cost $0.068157, generated Aug 14, 2026, 2:37 PM. Source
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
Protocol gradually-image-comparison-v1. Prompt SHA 256: 985a75b38642a9f0e5e0c0e0c67f1b7f67780d42bd2168fa24e9a7a7a94b0da6
Stable Diffusion 3.5 Large image SHA 256: e748006fe56e442ad347e3f994f18b86ee1739f20dcee063aa7a03ee710c5d54
SenseNova U1.5 Lite image SHA 256: c092b333f479c5b28ad33958d0e45f0fb0989970af02690079cf1398742c55b8
Infographic
Stable Diffusion 3.5 Large: fal, requested 1024x1024, n=1, seed=12166653711354006000, estimated cost $0.068157, generated Aug 14, 2026, 2:37 PM. Source
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
Protocol gradually-image-comparison-v1. Prompt SHA 256: ed65cb4e6a51e2336f8b149ad4cbb16e020f07d527ad94362e719d2dcf91d94f
Stable Diffusion 3.5 Large image SHA 256: 4eb0fd741ef42e6d3fee4b1280cdfb098a0a04009b139051963895892e349f1e
SenseNova U1.5 Lite image SHA 256: dcf8206386da05d11c35a6950309e61f08a504d440366226eac316328718f5ae
Product photography
Stable Diffusion 3.5 Large: fal, requested 1024x1024, n=1, seed=13346308312015933000, estimated cost $0.068157, generated Aug 14, 2026, 2:37 PM. Source
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
Protocol gradually-image-comparison-v1. Prompt SHA 256: c67fd71e91304458a2feef5c91efa8677260fab0c0099a29a2c52cb579f5b2f3
Stable Diffusion 3.5 Large image SHA 256: ea9a7401dee8859ec2cb96af9f7ca29a177ef2202f52f629d8ce9f5839bd4061
SenseNova U1.5 Lite image SHA 256: d425ed5236325ee28633f83cb00f3fd39181f7dd6df0e5408d8b1c07c6796107
Typography and layout
Stable Diffusion 3.5 Large: fal, requested 1024x1024, n=1, seed=16632333557910893000, estimated cost $0.068157, generated Aug 14, 2026, 2:37 PM. Source
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
Protocol gradually-image-comparison-v1. Prompt SHA 256: 2e012c3d14ee5dd02203a94f394ca80a5038cdebd6032b25a8b8a221f2255419
Stable Diffusion 3.5 Large image SHA 256: e2994b1883a245b1c8c447957d121ea89d93aafff149029aa4e8507dbb769f9a
SenseNova U1.5 Lite image SHA 256: df5c50fc54f03b972796f424999bd5991ff758a6b7abc00c212864aca3b124bc
The numbers at a glance
Stable Diffusion 3.5 Large
Rank 21 of 21
SenseNova U1.5 Lite
not in the arena
Stable Diffusion 3.5 Large
Rank 87 of 108
SenseNova U1.5 Lite
Rank 14 of 108
Stable Diffusion 3.5 Large
no API price
SenseNova U1.5 Lite
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.
Stable Diffusion 3.5 Large
- Subscription
- n/a No plan in Germany names exactly this model.
- Via API
- No API price known. Access: API, local.
- License
- Open weights.
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.
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.
| Kennzahl | Stable Diffusion 3.5 Large | SenseNova U1.5 Lite |
|---|---|---|
| Ratings | ||
| Arena ratingfrom votes by users, higher is better | 938 | n/a |
| Arena rank | Rank 21 of 21 | n/a |
| Arena votesmore votes, a safer rating | 23,396 | n/a |
| GraduallyBenchour own rating, 0 to 100 | 27 | 73 |
| GraduallyBench by task | ||
| Typography and layoutLegible text, hierarchy, and composition | 31 | 93 |
| Product photographyMaterials, reflections, and fine details | 17 | 84 |
| Character and detailAnatomy, clothing, and spatial consistency | 23 | 35 |
| InfographicNumbers, labels, and visual organization | 39 | 80 |
| API price | ||
| Per imagelower is better | n/a | n/a |
| 100 images | n/a | n/a |
| Profile | ||
| Released | Oct 22, 2024 | n/a |
| Weightsopen means: runs locally | open | open |
| Access | API, local | API, Web app, local |
| Parameters | 8.1 billion | not published |
| Largest output | 1 Megapixel | 4K |
| Plans in Germanynaming exactly this model | n/a | n/a |
API prices for one image at 1,024 × 1,024 pixels according to Artificial Analysis.
Sources: Stable Diffusion 3.5 Large model source (verified Aug 15, 2026) · SenseNova U1.5 Lite model source (verified Nov 2, 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 Stable Diffusion 3.5 Large and SenseNova U1.5 Lite from the same arena and category. Older model versions are not used as substitutes.
More comparisons
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