AuraFlow v0.3vs.Lumina-Image 2.0

Which one is better?

In our own test, Lumina-Image 2.0 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.

AuraFlow v0.3: Infographic, first image from the fixed test run — AuraFlow v0.37 out of 100

Lumina-Image 2.0: Infographic, first image from the fixed test run — Lumina-Image 2.016 out of 100

Result for “Infographic”:Lumina-Image 2.0 slightly ahead

Prompt given to both modelsCreate a square German infographic titled SO FUNKTIONIERT PHOTOSYNTHESE. Show exactly four numbered steps in this order: 1 LICHT, 2 WASSER, 3 CO₂, 4 ZUCKER + SAUERSTOFF. Use a clean editorial science style with one plant cross-section, simple arrows, high contrast, legible labels, and no other text.

What the rating looks at: Numbers, labels, and visual organization.

“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

AuraFlow v0.3: manual, local PyTorch 2.13.0, Diffusers 0.36.0; fal/AuraFlow-v0.3@2cd8588f04c886002be4571697d84654a50e3af3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=8761677709905735111; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:42 PM. Source

Lumina-Image 2.0: fal, requested 1024x1024, n=1, seed=provider random, estimated cost $0.150000, generated Nov 1, 2026, 9:38 PM. Source

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

AuraFlow v0.3 image SHA 256: 9d0f14ca671e82f18947b9a0d7d7587e372cb4f515ce028434fac4efbd937155

Lumina-Image 2.0 image SHA 256: 8747df0401d91598486735bfff5d6bac6c139727a8bc50c60bf7f697f678b85f

Infographic

AuraFlow v0.3: manual, local PyTorch 2.13.0, Diffusers 0.36.0; fal/AuraFlow-v0.3@2cd8588f04c886002be4571697d84654a50e3af3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=3793893866514060497; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:47 PM. Source

Lumina-Image 2.0: fal, requested 1024x1024, n=1, seed=provider random, estimated cost $0.150000, generated Nov 1, 2026, 9:38 PM. Source

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

AuraFlow v0.3 image SHA 256: d2a4ecc1c165bc861ca60133d9ff95dc9d5b1d5320763be92c8168ff8c3b8166

Lumina-Image 2.0 image SHA 256: b937b28f3c3209280c5828e18c85341d3ca443175020ca1e407dae035b5df14f

Product photography

AuraFlow v0.3: manual, local PyTorch 2.13.0, Diffusers 0.36.0; fal/AuraFlow-v0.3@2cd8588f04c886002be4571697d84654a50e3af3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=4682738952817248216; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:37 PM. Source

Lumina-Image 2.0: fal, requested 1024x1024, n=1, seed=provider random, estimated cost $0.150000, generated Nov 1, 2026, 9:38 PM. Source

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

AuraFlow v0.3 image SHA 256: 6889065a427cc29bc1c0a53b0ad0662eb24f4be885148b0ebb8f6d945bbd4749

Lumina-Image 2.0 image SHA 256: 74b79fcbad7565e29995c941d2b488d2edde884b307ed99e47fad994424e9dfc

Typography and layout

AuraFlow v0.3: manual, local PyTorch 2.13.0, Diffusers 0.36.0; fal/AuraFlow-v0.3@2cd8588f04c886002be4571697d84654a50e3af3; native 1024x1024, 1:1; one request, first output; steps=50, guidance=3.5, seed=7437917803059710684; mps for text encoder and denoising; cpu for native VAE decode; float16 for text encoder and transformer; float32 for VAE, generated Nov 2, 2026, 6:31 PM. Source

Lumina-Image 2.0: fal, requested 1024x1024, n=1, seed=provider random, estimated cost $0.150000, generated Nov 1, 2026, 9:37 PM. Source

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

AuraFlow v0.3 image SHA 256: b6c221541210743564f6921b5e0bbc227c4d2246f6410cb0c1779c7c58d9460d

Lumina-Image 2.0 image SHA 256: f132c159d659fb76c94cd82f1decb617c475b9c4095b177d02b73f09f2954df0

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

AuraFlow v0.3

not in the arena

n/a

Lumina-Image 2.0

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

AuraFlow v0.3

Rank 102 of 108

Lumina-Image 2.0

Rank 97 of 108

Price per imagedollars through the API · lower is better

n/a

AuraFlow v0.3

no API price

n/a

Lumina-Image 2.0

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.

AuraFlow v0.3

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

Lumina-Image 2.0

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	AuraFlow v0.3	Lumina-Image 2.0
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	12	18
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	11	18
Product photographyMaterials, reflections, and fine details	15	16
Character and detailAnatomy, clothing, and spatial consistency	16	23
InfographicNumbers, labels, and visual organization	7	16
API price
Per imagelower is better	n/a	n/a
100 images	n/a	n/a
Profile
Released	n/a	Jan 25, 2025
Weightsopen means: runs locally	open	open
Access	local	local
Parameters	7 billion	2.6 billion
Largest output	1,536 × 1,536 pixels	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: AuraFlow v0.3 model source (verified Nov 1, 2026) · Lumina-Image 2.0 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 AuraFlow v0.3 and Lumina-Image 2.0 from the same arena and category. Older model versions are not used as substitutes.

More comparisons

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