Best Stable Diffusion Model for 8GB VRAM (8GB VRAM)
The SD models that run great on an 8GB GPU
The best Stable Diffusion model for 8GB VRAM in 2026 is SDXL — it runs in ~7GB and generates a 1024px image in ~8 seconds on an RTX 4060. For near-instant drafts use SDXL Turbo; for the lowest VRAM and the biggest LoRA library use SD 1.5 (~4GB). SDXL and its finetunes (Pony, Juggernaut) are the quality sweet spot on 8GB — and unlike Flux, SDXL fits without heavy quantization.
Models that fit in 8GB VRAM
Tested reference: RTX 4060 / RTX 3070 (8GB). Figures are for a 1024px image.
| Model | Size | Build | VRAM used | Speed |
|---|---|---|---|---|
| WINNERSDXL 1.0 Best quality that fits 8GB natively — huge finetune + LoRA ecosystem. Automatic1111 / ComfyUI / Forge | 3.5B | FP16 | ~7GB | ~8s / image |
| SDXL Turbo 1–4 step — near-instant generation for ideation. ComfyUI SDXL Turbo | 3.5B | FP16 | ~7GB | ~1s / image |
| Pony / Juggernaut XL Popular SDXL finetunes — better characters/photoreal out of the box. Civitai checkpoint | 3.5B | FP16 | ~7GB | ~8s / image |
| SD 1.5 Lowest VRAM, largest LoRA/ControlNet library; lower base resolution (512px). Automatic1111 / ComfyUI | 0.9B | FP16 | ~4GB | ~4s / image |
What won't fit in 8GB
- ✗Flux.1 dev (FP16) (needs ~24GB) — For Flux on 8GB use a GGUF/NF4 build instead — see the Flux 8GB guide.
How to fit more in 8GB
- →SDXL fits 8GB natively — no quantization needed; enable ––medvram only if you also run ControlNet.
- →Use the SDXL base at 1024px; going to 1536px+ on 8GB needs tiled VAE to avoid OOM.
- →SD 1.5 is still the best pick for heavy ControlNet or animation workflows on 8GB.
Quick start
git clone https://github.com/comfyanonymous/ComfyUIDownload an SDXL model into models/checkpointsGo from “it runs” to actually building
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Start learning free →Frequently asked questions
Is 8GB VRAM enough for Stable Diffusion?
Yes — 8GB runs SDXL natively at ~8s/image (1024px) and SD 1.5 even faster. Only Flux needs quantization on 8GB; SDXL and its finetunes fit at full precision.
SDXL vs SD 1.5 on 8GB?
SDXL gives higher base quality and 1024px output (~7GB); SD 1.5 uses ~4GB, generates faster at 512px, and has the largest LoRA/ControlNet library. Choose SDXL for quality, SD 1.5 for lightweight/ControlNet work.
Can 8GB run Flux instead of SDXL?
Only a quantized Flux (GGUF Q4/NF4) build, at ~55–60s/image. SDXL is far faster on 8GB; use Flux when you specifically want its prompt adherence and text rendering.
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