Ideogram 4.5vs.LLaDA-Image

Which one is better?

In our own test both are on par. Neither is in the arena. LLaDA-Image has no API price.

Test images

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

Ideogram 4.5: Infographic, first image from the fixed test run — Ideogram 4.585 out of 100

LLaDA-Image: Infographic, first image from the fixed test run — LLaDA-Image33 out of 100

Result for “Infographic”:Ideogram 4.5 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

Ideogram 4.5: fal, requested 1024x1024, n=1, seed=676327336, prompt expansion disabled, quality low, estimated cost $0.030000, generated Nov 1, 2026, 8:44 PM. Source

LLaDA-Image: manual, 2.13.0 PyTorch, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image@e4e2703f410f7ddb6ee8d6b09dac6a8ec5093039; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0; seed=6428048197886116697; MPS generator; BF16 text/diffusion components, FP32 denoising latent, receipt-reported CPU FP32 native VAE decode; negative_prompt argument omitted (None default, not the manufacturer's empty-string example); MPS community PR @ 5395ce055da9975b09f71e21b865973d409bb3cd; official pinned text encoder uses eager MoE fallback and SDPA attention; other image-component attention paths were not independently captured by this review; no CUDA numerical equivalence claimed; MPS fallback permitted, actual fallback operations not measured; two submissions: the original request stopped at the 60-GiB free-space safeguard before image or latent (supervisor exit 143); one technical same-request/same-seed retry produced the retained first completed output; no quality reroll, generated Nov 3, 2026, 8:50 AM. Source

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

Ideogram 4.5 image SHA 256: 765cb852ecb10a396bad4bd18c2dc9fcc77221ffff3f0b94ef9eccf4d190b418

LLaDA-Image image SHA 256: a34d96894f5500c5bce2c16cca14ae09748f3aff4d47d15f8aff0d1be5749211

Infographic

Ideogram 4.5: fal, requested 1024x1024, n=1, seed=1482950298, prompt expansion disabled, quality low, estimated cost $0.030000, generated Nov 1, 2026, 8:44 PM. Source

LLaDA-Image: manual, 2.13.0 PyTorch, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image@e4e2703f410f7ddb6ee8d6b09dac6a8ec5093039; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0; seed=1354677768900879717; MPS generator; BF16 text/diffusion components, FP32 denoising latent, receipt-reported CPU FP32 native VAE decode; negative_prompt argument omitted (None default, not the manufacturer's empty-string example); MPS community PR @ 5395ce055da9975b09f71e21b865973d409bb3cd; official pinned text encoder uses eager MoE fallback and SDPA attention; other image-component attention paths were not independently captured by this review; no CUDA numerical equivalence claimed; MPS fallback permitted, actual fallback operations not measured, generated Nov 3, 2026, 8:56 AM. Source

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

Ideogram 4.5 image SHA 256: c97b4321e68bf1617a4dc96b5e1f9372344b09b9ff987f07d0e9813e6210c656

LLaDA-Image image SHA 256: cad67ad3f1a475d12bc2152840dc98657f81b5c7318c09a9e9fa40fbb433372f

Product photography

Ideogram 4.5: fal, requested 1024x1024, n=1, seed=1376877115, prompt expansion disabled, quality low, estimated cost $0.030000, generated Nov 1, 2026, 8:44 PM. Source

LLaDA-Image: manual, 2.13.0 PyTorch, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image@e4e2703f410f7ddb6ee8d6b09dac6a8ec5093039; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0; seed=152405017095880227; MPS generator; BF16 text/diffusion components, FP32 denoising latent, receipt-reported CPU FP32 native VAE decode; negative_prompt argument omitted (None default, not the manufacturer's empty-string example); MPS community PR @ 5395ce055da9975b09f71e21b865973d409bb3cd; official pinned text encoder uses eager MoE fallback and SDPA attention; other image-component attention paths were not independently captured by this review; no CUDA numerical equivalence claimed; MPS fallback permitted, actual fallback operations not measured, generated Nov 3, 2026, 1:02 AM. Source

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

Ideogram 4.5 image SHA 256: b9427281a64b3103f52f439b8797bd11763f813a8ef142bf79d96e936b349ae1

LLaDA-Image image SHA 256: 888e173c25c26ff1dcbfd07aad01ffc6a71cc7735099d3e943e60dfddfe31553

Typography and layout

Ideogram 4.5: fal, requested 1024x1024, n=1, seed=988679089, prompt expansion disabled, quality low, estimated cost $0.030000, generated Nov 1, 2026, 8:44 PM. Source

LLaDA-Image: manual, 2.13.0 PyTorch, Diffusers 0.39.0, Transformers 4.57.6; inclusionAI/LLaDA-Image@e4e2703f410f7ddb6ee8d6b09dac6a8ec5093039; native 1024x1024, 1:1; one request, first output; steps=50, guidance=5.0; seed=8778315039365154420; MPS generator; BF16 text/diffusion components, FP32 denoising latent, receipt-reported CPU FP32 native VAE decode; negative_prompt argument omitted (None default, not the manufacturer's empty-string example); MPS community PR @ 5395ce055da9975b09f71e21b865973d409bb3cd; official pinned text encoder uses eager MoE fallback and SDPA attention; other image-component attention paths were not independently captured by this review; no CUDA numerical equivalence claimed; MPS fallback permitted, actual fallback operations not measured, generated Nov 3, 2026, 12:40 AM. Source

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

Ideogram 4.5 image SHA 256: ebe1fe3dccf258807db9a9063c1034185c1b3e91f0d8c9bd86c53525d374dd9c

LLaDA-Image image SHA 256: 256a88541c9821a6242bb434fb520d4d6f0793c934c66acd1fd2e8edd8086b5d

The numbers at a glance

Arena ratingfrom votes by users · higher is better

n/a

Ideogram 4.5

not in the arena

n/a

LLaDA-Image

not in the arena

GraduallyBenchour own rating, 0 to 100 · higher is better

Ideogram 4.5

Rank 45 of 108

LLaDA-Image

Rank 63 of 108

Price per imagedollars through the API · lower is better

$0.10

Ideogram 4.5

expensive

n/a

LLaDA-Image

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.

Ideogram 4.5

Subscription: No Ideogram subscription includes this model. Through other providers from ≈ €9.54 a month (Krea Basic, with limited credits). 33 plans in Germany.
Via API: $0.10 per image, 100 images $10.
Weights: unknown.

LLaDA-Image

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 · API prices from Nov 6, 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	Ideogram 4.5	LLaDA-Image
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	63	48
GraduallyBench by task
Typography and layoutLegible text, hierarchy, and composition	28	62
Product photographyMaterials, reflections, and fine details	69	35
Character and detailAnatomy, clothing, and spatial consistency	68	63
InfographicNumbers, labels, and visual organization	85	33
API price
Per imagelower is better	$0.10	n/a
100 images	$10	n/a
Profile
Released	n/a	Sep 4, 2026
Weightsopen means: runs locally	unknown	open
Access	API	local
Parameters	not published	6 billion
Largest output	not consistently published	not consistently published
Plans in Germanynaming exactly this model	33	n/a

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

Sources: Ideogram 4.5 model source (verified Nov 1, 2026) · LLaDA-Image 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 Ideogram 4.5 and LLaDA-Image from the same arena and category. Older model versions are not used as substitutes.

More comparisons

Compare Ideogram 4.5 and LLaDA-Image with the models people compare them with most often.

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