MiniMax Image-01vs.SANA-1.5 4.8B 1024px

Which one is better?

In our own test, MiniMax Image-01 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.

MiniMax Image-01: Character and detail, first image from the fixed test run — MiniMax Image-0133 out of 100

SANA-1.5 4.8B 1024px: Character and detail, first image from the fixed test run — SANA-1.5 4.8B 1024px0 out of 100

Result for “Character and detail”:MiniMax Image-01 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

MiniMax Image-01: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.010000, generated Nov 1, 2026, 8:43 PM. Source

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=6914427587596023045; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:42 PM. Source

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

MiniMax Image-01 image SHA 256: b99793e66d1eb69880872d1865f25456b6588dc658aa46906b7636da46f63320

SANA-1.5 4.8B 1024px image SHA 256: 97badf740db81367de7d6af73cc9313f1dfc4fe8383183ddbd9fc12cc67b35ee

Infographic

MiniMax Image-01: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.010000, generated Nov 1, 2026, 8:43 PM. Source

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=3447101042619426797; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:43 PM. Source

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

MiniMax Image-01 image SHA 256: 31b08957fb9eda45525c50935fd332cdbe5a5150a4ed57dead5254e667b2b0de

SANA-1.5 4.8B 1024px image SHA 256: 6c23b2df82d085e155c012c16915d04dd3a1aacdb78c9604eb74668309e07b38

Product photography

MiniMax Image-01: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.010000, generated Nov 1, 2026, 8:43 PM. Source

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=1122699157863902383; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:41 PM. Source

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

MiniMax Image-01 image SHA 256: a8986bd9a5e8262b5705f8a7ba5259968371a3bc8e14394b992736f59e45385b

SANA-1.5 4.8B 1024px image SHA 256: 0ceaa96a83bc85d12c7f56b925226a346ee9b42f831fa5a9592edc4fc1e7ce81

Typography and layout

MiniMax Image-01: fal, aspect ratio 1:1, n=1, seed=provider random, estimated cost $0.010000, generated Nov 1, 2026, 8:42 PM. Source

SANA-1.5 4.8B 1024px: manual, local PyTorch 2.13.0, Diffusers 0.36.0; Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers@9468102c3cebb657f8c4b5f1e5a71e989a15f10d; native 1024x1024, 1:1; one request, first output; steps=20, guidance=4.5, seed=623973358981804157; mps for text encoder and denoising; cpu for native VAE decode; bfloat16 for text encoder and transformer; float32 for VAE; native prompt preprocessing lowercases input; optional instruction disabled, generated Nov 2, 2026, 5:40 PM. Source

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

MiniMax Image-01 image SHA 256: 020129f518174bf171032cc5cb7b2234782f4e1d7b1e685d473388094630a107

SANA-1.5 4.8B 1024px image SHA 256: 8371e0e35ad4472b71165cedd1940eb0339b19c24f801c3b956874c090a327fc

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

MiniMax Image-01

not in the arena

n/a

SANA-1.5 4.8B 1024px

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

MiniMax Image-01

Rank 82 of 108

SANA-1.5 4.8B 1024px

Rank 106 of 108

Price per imagedollars through the API · lower is better

n/a

MiniMax Image-01

no API price

n/a

SANA-1.5 4.8B 1024px

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.

MiniMax Image-01

Subscription: n/a No plan in Germany names exactly this model.
Via API: No API price known. Access: API.
Weights: unknown.

SANA-1.5 4.8B 1024px

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	MiniMax Image-01	SANA-1.5 4.8B 1024px
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	31	4
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	37	8
Product photographyMaterials, reflections, and fine details	30	1
Character and detailAnatomy, clothing, and spatial consistency	33	0
InfographicNumbers, labels, and visual organization	26	6
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	Feb 28, 2025	Mar 16, 2025
Weightsopen means: runs locally	unknown	open
Access	API	local
Parameters	not published	4.8 billion
Largest output	not consistently published	not consistently published
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: MiniMax Image-01 model source (verified Nov 1, 2026) · SANA-1.5 4.8B 1024px 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 MiniMax Image-01 and SANA-1.5 4.8B 1024px from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare MiniMax Image-01 and SANA-1.5 4.8B 1024px with the models people compare them with most often.

Compare another matchup

First image modelSecond image model