Illustrious XL / Pony (SDXL anime) VRAM requirements
The two big anime families built on SDXL. Almost every anime checkpoint on Civitai (WAI, NoobAI and friends) has this same size and fits exactly like SDXL.
01The files, and how much VRAM each needs
| File | Size | Needed | Min. VRAM | Quality | Source |
|---|---|---|---|---|---|
| 16-bit | 6.9 GB | 7.1 GB | 8 GB | the original weights | OnomaAIResearch/Illustrious-xl-early-release-v0 → |
| Q8_0 | 2.7 GB | 4.7 GB | 5 GB | practically identical to the original | calcuis/illustrious → |
| FP8 | 3.5 GB | 5.5 GB | 6 GB | practically identical to the original | calcuis/illustrious → |
| Q6_K | 2.1 GB | 4.1 GB | 5 GB | very close to the original | calcuis/illustrious → |
| Q5_K_M | 1.8 GB | 3.8 GB | 4 GB | close; small differences in fine detail | calcuis/illustrious → |
| Q4_K_M | 1.5 GB | 3.5 GB | 4 GB | good; some loss in fine detail and text | calcuis/illustrious → |
| Q3_K_M | 1.2 GB | 3.2 GB | 4 GB | noticeable loss of detail | calcuis/illustrious → |
| Q2_K | 0.9 GB | 2.9 GB | 3 GB | heavy loss; a last resort | calcuis/illustrious → |
“Needed” = file + 1.2 GB working memory + 0.8 GB system reserve. The 6.94 GB checkpoint holds the UNet plus text encoders and VAE; only the UNet (about 5.1 GB) sits in VRAM while sampling. The GGUF and FP8 files from calcuis contain the UNet only.
02By amount of VRAM
03Best GPU for Illustrious / Pony
The cheapest cards (by launch price) that run it well, and every card sorted by memory: best GPU for Illustrious / Pony → Planning bigger images or longer clips? Open the calculator →
04By graphics card
| GPU | VRAM | Verdict | Best file | Needed |
|---|---|---|---|---|
| Desktop graphics cards | ||||
| RTX 2060 6 GB | 6 GB | Runs well | Q8_0 | 4.7 GB |
| RTX 3050 6 GB | 6 GB | Runs well | Q8_0 | 4.7 GB |
| RTX 2070 Super 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2080 Super 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3050 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3060 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3060 Ti 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3070 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3070 Ti 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4060 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4060 Ti 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5050 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5060 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5060 Ti 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 7600 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 9050 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 9060 XT 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| Arc B570 10 GB | 10 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 10 GB | 10 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2080 Ti 11 GB | 11 GB | Runs well | 16-bit | 7.1 GB |
| Arc B580 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2060 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3060 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 Ti 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4070 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4070 Super 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4070 Ti 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5070 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RX 7700 XT 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RX 9070 GRE 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| Arc A770 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4060 Ti 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4070 Ti Super 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4080 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4080 Super 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5060 Ti 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5070 Ti 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5080 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 7600 XT 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 7800 XT 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 7900 GRE 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 9060 XT 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 9070 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 9070 XT 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 7900 XT 20 GB | 20 GB | Runs well | 16-bit | 7.1 GB |
| Arc Pro B60 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3090 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3090 Ti 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4090 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| RX 7900 XTX 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| Arc Pro B70 32 GB | 32 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5090 32 GB | 32 GB | Runs well | 16-bit | 7.1 GB |
| Laptop GPUs | ||||
| RTX 3050 Laptop 4 GB | 4 GB | Runs | Q5_K_M | 3.8 GB |
| RTX 3050 Ti Laptop 4 GB | 4 GB | Runs | Q5_K_M | 3.8 GB |
| RTX 2060 Laptop 6 GB | 6 GB | Runs well | Q8_0 | 4.7 GB |
| RTX 3050 Laptop 6 GB | 6 GB | Runs well | Q8_0 | 4.7 GB |
| RTX 3060 Laptop 6 GB | 6 GB | Runs well | Q8_0 | 4.7 GB |
| RTX 4050 Laptop 6 GB | 6 GB | Runs well | FP8 | 5.5 GB |
| RTX 2070 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2070 Super Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2080 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 2080 Super Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3070 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3070 Ti Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4060 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4070 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5050 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5060 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5070 Laptop 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 7600M 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 7600M XT 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 7600S 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RX 7700S 8 GB | 8 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4080 Laptop 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5070 Laptop 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5070 Ti Laptop 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RX 7800M 12 GB | 12 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 Laptop 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 3080 Ti Laptop 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 4090 Laptop 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5080 Laptop 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RX 7900M 16 GB | 16 GB | Runs well | 16-bit | 7.1 GB |
| RTX 5090 Laptop 24 GB | 24 GB | Runs well | 16-bit | 7.1 GB |
| Unified memory | ||||
| Radeon 8060S (Strix Halo) 96 GB | 96 GB | Runs well | 16-bit | 7.1 GB |
| Apple Silicon Macs (by memory) | ||||
| Mac 16 GB | 12.7 GB | Runs well | 16-bit | 7.1 GB |
| Mac 18 GB | 14.4 GB | Runs well | 16-bit | 7.1 GB |
| Mac 24 GB | 19.6 GB | Runs well | 16-bit | 7.1 GB |
| Mac 32 GB | 26.8 GB | Runs well | 16-bit | 7.1 GB |
| Mac 36 GB | 30.2 GB | Runs well | 16-bit | 7.1 GB |
| Mac 48 GB | 40.2 GB | Runs well | 16-bit | 7.1 GB |
| Mac 64 GB | 55.7 GB | Runs well | 16-bit | 7.1 GB |
| Mac 96 GB | 85 GB | Runs well | 16-bit | 7.1 GB |
| Mac 128 GB | 115.4 GB | Runs well | 16-bit | 7.1 GB |
| Mac 192 GB | 175.4 GB | Runs well | 16-bit | 7.1 GB |
| Mac 256 GB | 236.9 GB | Runs well | 16-bit | 7.1 GB |
| Mac 512 GB | 498.1 GB | Runs well | 16-bit | 7.1 GB |
On RTX 40/50 GPUs the FP8 file is preferred over Q8_0 when both fit (hardware FP8). All verdicts are calculated; see how the numbers work.
05Text encoder, VAE and other files
The text encoder is inside the checkpoint, so there is nothing extra to download.
06Where the files go in ComfyUI
| File | Folder | Loader node |
|---|---|---|
| The checkpoint (.safetensors) | ComfyUI/models/checkpoints | Load Checkpoint |
| GGUF file (.gguf) | ComfyUI/models/unet | Unet Loader (GGUF) — from the ComfyUI-GGUF node pack |
Standard ComfyUI folders. After copying files, press R in ComfyUI (or restart it) to refresh the lists. Some uploads need their uploader's own loader node — see the notes above.
07AMD, Intel and NVIDIA: which file types are fast
| File type | RTX 50 | RTX 40 | RTX 30 / 20 | RX 9000 | RX 7000/6000 · Strix Halo | Intel Arc |
|---|---|---|---|---|---|---|
| 16-bit | Runs | Runs | Runs | Runs | Runs | Runs |
| FP8 | Native FP8 | Native FP8 | No FP8 speed-up | Native FP8 | No FP8 speed-up | No FP8 speed-up |
| GGUF | Runs (GGUF node) | Runs (GGUF node) | Runs (GGUF node) | Runs (GGUF node) | Runs (GGUF node) | Runs (GGUF node) |
Every file type loads on every listed GPU, so the memory verdicts apply to all of them. What differs is speed: FP8 maths needs RTX 40/50 or RX 9000 (with ROCm 6.4+ and PyTorch 2.7+); ComfyUI's INT8 maths runs on NVIDIA and AMD, not on Intel; GGUF is unpacked on the fly on any GPU, which costs some speed. NVFP4 files are fast only on RTX 50. AMD runs ComfyUI on Windows through ROCm, Intel through PyTorch XPU; some custom nodes are NVIDIA-only. Source: ComfyUI model_management.py. AMD and Intel guide →
08Measured and reported results
| Label | GPU | Setup | Result | Peak VRAM | Date | Source |
|---|---|---|---|---|---|---|
| reported | RTX 3060 Ti 8 GB | Illustrious-XL-v2.0 · 1024x1024 “NVIDIA RTX 3060 Ti | 1.96it/s | 0.51s/it | CUDA 12.9 | ComfyUI (Unknown) | Ubuntu Server 24.04.2 LTS” Community speed list; ComfyUI, Euler/Normal, CFG 8, square 1:1, batch speed only (no per-image time); date = list last-updated date; SDXL 1024px section | 0.51 s/it | — | 2025-11-29 | huggingface.co → |
| reported | RTX 3090 24 GB | Illustrious-XL-v2.0 · 1024x1024 “NVIDIA RTX 3090 | 4.00it/s | 0.25s/it | CUDA 12.9 | ComfyUI (Unknown) | Arch Linux” Community speed list; ComfyUI, Euler/Normal, CFG 8, square 1:1, batch speed only (no per-image time); date = list last-updated date; SDXL 1024px section | 0.25 s/it | — | 2025-11-29 | huggingface.co → |
| reported | RTX 4060 Laptop 8 GB | WAI-Illustrious SDXL v16.0 · 1024x1024 · 20 steps “1024x1024 | 1.47 | 13s | 15.81s | ~5.6GB” ComfyUI, euler_ancestral/Karras CFG 5; columns it/s | KSampler | total | VRAM; no --lowvram; VRAM approximate | 15.81 s / image · 1.47 it/s | 5.6 GB | 2026-02-26 | lilting.ch → |
| reported | RTX 4090 24 GB | Illustrious-XL-v2.0 · 1024x1024 “NVIDIA RTX 4090 | 7.00it/s | 0.14s/it | CUDA 12.9 | ComfyUI (Unknown) | Windows 11 24H2” Community speed list; ComfyUI, Euler/Normal, CFG 8, square 1:1, batch speed only (no per-image time); date = list last-updated date; SDXL 1024px section | 0.14 s/it | — | 2025-11-29 | huggingface.co → |
| reported | RTX 5060 Ti 16 GB | Illustrious-XL-v2.0 · 1024x1024 “NVIDIA RTX 5060 Ti | 2.60it/s | 0.39s/it | CUDA 12.9 | ComfyUI (Unknown) | Arch Linux” Community speed list; ComfyUI, Euler/Normal, CFG 8, square 1:1, batch speed only (no per-image time); date = list last-updated date; SDXL 1024px section; row says 'RTX 5060 Ti', co | 0.39 s/it | — | 2025-11-29 | huggingface.co → |
| reported | RTX 5090 32 GB | Illustrious-XL-v2.0 · 1024x1024 “NVIDIA RTX 5090 | 8.95it/s | 0.11s/it | CUDA 12.8 | ComfyUI (Unknown) | Windows 11 24H2” Community speed list; ComfyUI, Euler/Normal, CFG 8, square 1:1, batch speed only (no per-image time); date = list last-updated date; SDXL 1024px section | 0.11 s/it | — | 2025-11-29 | huggingface.co → |
Reported results are other people's numbers, copied as published, with a link. Settings, drivers and ComfyUI versions differ, so compare them with care. Send yours.
09Training a LoRA for Illustrious / Pony
No trainer documentation with a VRAM figure for this model was found yet. What the trainers say for other models →
10Every file tracked for Illustrious / Pony
| File | Type | Size | Repo |
|---|---|---|---|
| ponyDiffusionV6XL_v6StartWithThisOne.safetensors (pony-v6) | 16-bit | 6.94 GB | LyliaEngine/Pony_Diffusion_V6_XL → all-in-one checkpoint: includes text encoder(s) and VAE, not diffusion-model-only |
| Illustrious-XL-v0.1.safetensors (illustrious-v0.1) | 16-bit | 6.94 GB | OnomaAIResearch/Illustrious-xl-early-release-v0 → all-in-one checkpoint: includes text encoder(s) and VAE, not diffusion-model-only (CLIP-L + CLIP-G + VAE) |
| Illustrious-XL-v0.1-GUIDED.safetensors (illustrious-v0.1-guided) | 16-bit | 6.94 GB | OnomaAIResearch/Illustrious-xl-early-release-v0 → all-in-one checkpoint: includes text encoder(s) and VAE, not diffusion-model-only |
| illustrious-f16.gguf (illustrious) | F16 | 5.14 GB | calcuis/illustrious → |
| illustrious_fp8_e4m3fn.safetensors (illustrious) | FP8 | 3.47 GB | calcuis/illustrious → all-in-one checkpoint: includes text encoder(s) and VAE, not diffusion-model-only (per repo README: fp8 file includes VAE and CLIPs) |
| illustrious-q8_0.gguf (illustrious) | Q8_0 | 2.74 GB | calcuis/illustrious → |
| illustrious-q6_k.gguf (illustrious) | Q6_K | 2.12 GB | calcuis/illustrious → |
| illustrious-q5_1.gguf (illustrious) | Q5_1 | 1.94 GB | calcuis/illustrious → |
| illustrious-q5_k_m.gguf (illustrious) | Q5_K_M | 1.81 GB | calcuis/illustrious → |
| illustrious-q5_0.gguf (illustrious) | Q5_0 | 1.78 GB | calcuis/illustrious → |
| illustrious-q5_k_s.gguf (illustrious) | Q5_K_S | 1.78 GB | calcuis/illustrious → |
| illustrious-q4_1.gguf (illustrious) | Q4_1 | 1.62 GB | calcuis/illustrious → |
| illustrious-q4_k_m.gguf (illustrious) | Q4_K_M | 1.53 GB | calcuis/illustrious → |
| illustrious-q4_k_s.gguf (illustrious) | Q4_K_S | 1.46 GB | calcuis/illustrious → |
| illustrious-q4_0.gguf (illustrious) | Q4_0 | 1.46 GB | calcuis/illustrious → |
| illustrious-q3_k_l.gguf (illustrious) | Q3_K_L | 1.19 GB | calcuis/illustrious → |
| illustrious-q3_k_m.gguf (illustrious) | Q3_K_M | 1.15 GB | calcuis/illustrious → |
| illustrious-q3_k_s.gguf (illustrious) | Q3_K_S | 1.12 GB | calcuis/illustrious → |
| illustrious-q2_k.gguf (illustrious) | Q2_K | 0.89 GB | calcuis/illustrious → |
SDXL architecture (UNet ~2.6B, 3.5B incl. text encoders) - fits exactly like SDXL. Illustrious XL and Pony V6 are the two main anime base families; most people run Civitai fine-tunes (WAI, NoobAI, etc.) that are the same 6.94 GB all-in-one size. HF downloads: Pony mirror ~289k, Illustrious v0.1 ~81k.