Best Local Anime Image Model: Illustrious vs NoobAI

Short answer: on 8GB, download Animagine XL 4.0 if you want commercial rights and forgiving defaults, Illustrious XL v1.0 if you want the largest LoRA ecosystem and native 1536x1536, and NoobAI XL 1.1 if you want the deepest booru tag coverage and can live with a non-commercial licence. All three are SDXL checkpoints of much the same size — 6.94GB for Illustrious and Animagine, 7.11GB for NoobAI, per the Hugging Face file listings. The fourth option, Anima, is a ~2.9B model with community GGUF quants as small as 1.02GB — the only one of the four that fits 8GB comfortably rather than barely.

But the model you pick is probably not why your output looks bad. The prompt syntax is not transferable between these bases, and nobody says so on the download page. You grabbed a 6.5GB Illustrious merge, pasted in the prompt that worked on your last checkpoint, and got mush. That is not a bad model. That is four different tag vocabularies wearing the same file extension.

This page is the comparison the SERP does not have: what each base actually wants in the prompt box, which licence lets you sell the output, and honest 8GB arithmetic — including a clear statement of what we did not measure.

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The Verdict First

Pick by constraint, not by which one is "best" — they are close enough in quality that the licence and the prompt style decide it.

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Why Your Output Is Mush

These are booru-tag models, and a tag model given a sentence has almost nothing to condition on. SDXL-derived anime checkpoints were finetuned on images captioned with comma-separated Danbooru or e621 tags plus a quality-tier vocabulary. Type "a beautiful anime girl standing in the rain, highly detailed, cinematic" and you are describing an image in a language the finetune spent very little of its budget learning.

Three specific failure modes, in the order they usually bite:

1. No quality tags. Booru datasets are mostly mediocre art, because the internet is. Finetunes encode that with a tier vocabulary so you can steer away from the mean. NoobAI 1.1's card ties its tiers to popularity percentiles — masterpiece above the 95th percentile, best quality 85th-95th, good quality 60th-85th, normal quality 30th-60th, worst quality at or below the 30th. Omit them and you get the 50th percentile of Danbooru. That is your mush.

2. Wrong CFG for the base. Animagine XL 4.0 recommends CFG 4-7, 5 preferred, at 25-28 steps with Euler Ancestral. NoobAI 1.1 recommends CFG 5-6, 25-30 steps, Euler a. Anima recommends CFG 3.5-5 at 28-50 steps. Arriving from photoreal SDXL work at CFG 7.5 puts you above all three, and over-CFG on an anime finetune looks exactly like "deformed and oversaturated."

3. Missing the negative prompt. These cards publish one for a reason. Animagine's is long and specific: lowres, bad anatomy, bad hands, text, error, missing finger, extra digits, fewer digits, cropped, worst quality, low quality, low score, bad score, average score, signature, watermark, username, blurry. NoobAI's includes furry/anthro terms (mammal, anthro, furry, ambiguous form, feral, semi-anthro) precisely because it also trained on e621 — a detail that will surprise you if you skip it.

If your setup itself is the problem rather than the prompt, start with our Stable Diffusion local install guide; if generations fail rather than disappoint, ComfyUI's full guide covers the workflow layer.

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The Four Bases, Compared

Every figure below comes from the official model card or Hugging Face repository listing, fetched August 2026. Nothing here is our own benchmark.

A few things that table makes obvious. These are not four independent models — NoobAI is a finetune of Illustrious, which is a finetune of SDXL, so their tag vocabularies overlap heavily even though their recommended prefixes differ. Anima is the genuine outlier: a different architecture lineage entirely (NVIDIA's Cosmos-Predict2), a much smaller parameter count, and the only one with a 2026 knowledge cutoff.

And the download numbers are worth reading carefully. Animagine XL 4.0's 257,087 monthly downloads is real distribution. The base Anima's 816,639 downloads and 2.09k likes make it the most-pulled of the group — but that is the 2B base, not the 2.9B depth-expanded derivative in this table, which sits at 23,202.

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Prompt Syntax Per Model

This is the section the rest of the internet skips. Each card publishes a different template, and using the wrong one is the single biggest quality lever available to you.

Animagine XL 4.0 — strict ordering

The card gives the order explicitly:

1girl/1boy/1other, character name, from which series, rating,
everything else in any order, end with quality enhancement

Its quality vocabulary is masterpiece, best quality, low quality, worst quality, and it carries a separate score-tag scale: high score, great score, good score, average score, bad score, low score. Those are two different knobs, and both belong in the prompt. Settings: Euler a, 28 steps, CFG 5, 1024x1024 or one of the published aspect ratios.

NoobAI XL 1.1 — prefix, then structure

The card's recommended prefix is verbatim:

masterpiece, best quality, newest, absurdres, highres, safe,

Then its caption structure: character count, series, artists, special tags, general tags, other tags. The distinctive piece is date tags — old (2005-2010), early (2011-2014), mid (2014-2017), recent (2018-2020), newest (2021-2024). Putting newest in your prefix is what pulls the style toward contemporary booru art rather than a 2008 average. Animagine has no equivalent tag, so that word is doing nothing for you there. Settings: Euler a, 25-30 steps, CFG 5-6, 832x1216.

Illustrious XL v1.0 — the flexible one

Illustrious's card is the least prescriptive: it describes support for "advanced natural language processing with concise Danbooru tag-based prompts," and says you can use plain English descriptions, precise tags, or both. That flexibility is why so much of the ecosystem is built on it — and also why "just prompt it normally" advice about Illustrious gets copy-pasted onto NoobAI, where it does not hold. The card publishes no recommended CFG or step count, so start where its descendants sit (CFG 5-6, ~28 steps) and tune.

Anima — detail over brevity

Anima's guidance is blunt: "THE MORE DETAILED THE PROMPT, THE BETTER." The recommended components are quality tags, year/period tags, artist tags, character count, character tags in Danbooru/Gelbooru format, series/copyright tags, and base appearance. Note that this is still a tag-flavoured model rather than a pure natural-language one — the difference is prompt length and specificity, not a switch to prose. Its card also notes that no score tags were included in training, so the score vocabulary you learned on Animagine is dead weight here. Settings: Euler or Res-multistep, sgm-uniform / beta / linear-quadratic scheduler, 28-50 steps, CFG 3.5-5, 812x1216 or 1152x1536 (the card flags 1536x1536 as "iffy").

The practical rule: keep four saved prompt templates, not one. Swapping checkpoints without swapping template is how a perfectly good 7GB download gets written off as broken.

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The Licence Trap

Three of these four models restrict something, and the restrictions are not the same shape. Read this before you build a business on one.

Animagine XL 4.0 — CreativeML Open RAIL++-M. The permissive option of the group. OpenRAIL++-M allows commercial use subject to the licence's behavioural use restrictions. If you want the least friction between generating and selling, this is the download.

NoobAI XL 1.1 — fair-ai-public-license-1.0-sd. Carries a commercial prohibition and an open-source-derivative requirement. If you finetune or merge it, the licence has opinions about what you must publish. This is the trap that catches people who assume "on Hugging Face" means "free to use commercially."

Anima — CircleStone Labs Non-Commercial License, with a genuinely useful carve-out that the card states plainly: "The non-commercial restriction applies only to the Model, and not to Outputs." Selling images, accepting paid commissions and using generated imagery as assets in commercial products are explicitly permitted. What is restricted is the weights — API hosting, paid platforms, embedding the model in a monetised product. Licensing enquiries go to the contact address on the model card. So: you can sell the art, you cannot sell access to the model.

Illustrious XL v1.0 is tagged sdxl-license on Hugging Face, with no separate LICENSE file in the repository listing. Given the size of the Illustrious merge ecosystem, this is the one where you most need to check the specific file rather than the base.

The merge problem applies to all four. The checkpoint you downloaded from a model-sharing site is very likely a merge of two or more of these, and a merge does not get to pick the most permissive parent's terms. Whatever it says on the file you actually have is what governs you. We are not lawyers and this is not legal advice — it is a prompt to go read the licence attached to your download.

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What Actually Runs on 8GB

The arithmetic, stated as arithmetic — we did not benchmark these on an 8GB card, and we are not going to pretend otherwise.

The three SDXL checkpoints are 6.9-7.1GB fp16 files — 6.94GB for Illustrious-XL-v1.0 and animagine-xl-4.0, 7.11GB for NoobAI-XL-v1.1, read off the Hugging Face repository listings. Loading fp16 weights of that size onto an 8GB card leaves roughly a gigabyte for the VAE decode, both text encoders, the latents, the sampler's working memory, and whatever your display is already holding. That is not a comfortable margin — it is the margin where a resolution bump or a second LoRA tips you into out-of-memory.

What to check on your own card, in this order:

• Resolution first. 1536x1536 is 2.25x the pixel area of 1024x1024, and latent and attention memory scale with area. If Illustrious OOMs at native resolution on 8GB, that is expected — generate at 1024 and upscale.
• Weight precision second. fp8 weights roughly halve the checkpoint's footprint versus fp16. This is the standard 8GB move for SDXL-class models and it costs some quality.
• Offloading third. Sequential CPU offload will make almost anything fit, at a speed cost that is severe rather than mild. It is a fallback, not a plan.
• VAE tiling for the decode step, which is often where the OOM actually happens rather than during sampling.

Anima is the honest 8GB answer. At ~2.9B parameters with community GGUF quants — Q3_K_M at 1.02GB, Q4_K_S 1.27GB, Q4_K_M 1.38GB, Q5_K_M 1.56GB, Q6_K 1.74GB, Q8_0 2.24GB — it is not close to filling an 8GB card. The quant repo's own instructions are to install the ComfyUI-GGUF custom nodes, place the files in ComfyUI/models/unet/, and load with the Unet-Loader (GGUF) node, with the text encoder and VAE taken from the original Anima release. We have not run this ourselves, and one caveat is load-bearing: those GGUF quants are published against the 2B base Anima, not the 2.9B depth-expanded build. Verify which weights you are pulling before you plan around the file sizes.

For general-purpose 8GB picks outside the anime niche, our best Stable Diffusion model for 8GB VRAM page covers the wider field, and best GPU for image generation covers what changes when you move up a tier.

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Which One Should You Download

One model, one weekend, one prompt template. Do not download three at once — that is how you end up with 21GB of checkpoints and no idea which one was good.

• First anime checkpoint ever, 8GB card: Animagine XL 4.0. The clearest documentation of the four, published settings that work at their defaults, and a licence you do not have to think about.
• You want a specific character or style LoRA: Illustrious XL v1.0, because that is where the ecosystem lives — its HF page counts 11 adapters, 92 finetunes and 98 merges. If your LoRA is Illustrious-based, the base matters more than your preference does. Training your own is covered in our image LoRA training guide.
• You want obscure characters and artist styles: NoobAI XL 1.1, for the Danbooru-to-late-2024 plus e621 coverage. Accept the non-commercial licence going in.
• You are VRAM-poor or want post-2024 knowledge: Anima, via GGUF, with the provenance caveats above.
• You also want photoreal output: none of these. Anime finetunes trade photoreal ability away deliberately — see best local image models compared for FLUX and Qwen, or SDXL vs FLUX for the architecture trade-off. If your interest is uncensored generation specifically, that is a different page.

Whatever you pick, generating at 1024 and running a dedicated upscale pass beats fighting your card for native 1536 — our local AI image upscaling guide covers the tools.

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What We Did Not Test

Being direct about the gaps, because a comparison page that hides them is worth less than one that does not:

• No side-by-side generations of our own. We did not run a matched prompt through all four bases at matched steps and CFG. Every settings and syntax figure on this page is quoted from the official model card, attributed, and dated — not measured by us. Take the prompt-format guidance as authoritative (it is the publisher's own) and the aesthetic ranking as absent, which it is on purpose.
• No 8GB VRAM measurement. The 6.94GB and 7.11GB figures are file sizes from Hugging Face, and the memory discussion is arithmetic plus the standard mitigations. We have not measured peak VRAM at 1024 or at 1536x1536 on an 8GB card.
• No confirmation that Anima's GGUF quants load in ComfyUI. The loader instructions above are the quant repo's own. And the quants target the 2B base rather than the 2.9B build, which is exactly the sort of mismatch that produces a confusing failure.
• Anima's provenance is thinner than the others'. The 2.9B build is a single-uploader "preview-v1" derivative. The base it comes from is not thin at all — 816,639 monthly downloads, 2.09k likes, published in collaboration with Comfy Org — but the depth-expanded derivative is community work and should be treated as such.
• NoobAI 1.1 is not the newest NoobAI. A later v-prediction variant exists (noobai-XL-Vpred-1.0, dated November 2025). We kept 1.1 in the comparison because v-pred checkpoints require explicit tooling support and are a different setup problem.

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Sources

• cagliostrolab/animagine-xl-4.0 — licence, prompt ordering, quality and score tags, CFG/steps/sampler, resolutions, negative prompt, 6.94GB file, 8.4M-image dataset with a 7 January 2025 knowledge cutoff, 257,087 downloads last month (fetched August 2026)
• Laxhar/noobai-XL-1.1 — fair-ai-public-license-1.0-sd, base lineage, Danbooru/e621 training range, prefix and negative prompt, quality percentile tiers, date tags, CFG 5-6 / 25-30 steps, 7.11GB file, 95,298 downloads last month
• OnomaAIResearch/Illustrious-XL-v1.0 — sdxl-license tag, native 1536x1536, prompt flexibility, June 2024 knowledge, 6.94GB checkpoint, adapter/finetune/merge counts
• circlestone-labs/Anima and Gazingstars123/Anima-2.9B — licence terms including the outputs carve-out, parameter counts, Cosmos-Predict2 lineage, prompting guidance, settings, July 2026 cutoff, download and like counts
• Abiray/Anima-base-v1.0-GGUF — GGUF quant sizes and the ComfyUI-GGUF loader instructions

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