image model · stable-diffusion · Linux
Can I run Stable Diffusion XL 1.0 on Nvidia DGX Spark (128GB)?
Yes. Stable Diffusion XL 1.0 runs on Nvidia DGX Spark (128GB) at fp16 (~7.5 GB of ~112 GB usable).
Runs at fp16 using ~7.5 GB of ~112 GB usable.
- Peak VRAM
- ~7.5 GB
- Usable on device
- ~112 GB
- Device memory
- 128 GB
- Quant
- fp16
How to run it
Use ComfyUI or AUTOMATIC1111 / Forge at fp16. It conditions on an image, not a text prompt; the pipeline offloads each stage off the GPU between passes, keeping peak VRAM near the active stage.
- Type
- image (UNET)
- Parameters
- 2.6B
- Peak VRAM
- ~7.5 GB at fp16
- Resolution
- 1024×1024
- License
- CreativeML OpenRAIL++-M
- Memory
- 128 GB unified
- Usable for weights
- ~112 GB
- Power draw
- ~140 W
- Best runtime
- llama.cpp (CUDA) / Ollama (CUDA)
You could also run
Run Stable Diffusion XL 1.0 on other hardware
FAQ
Can Nvidia DGX Spark (128GB) run Stable Diffusion XL 1.0?
Yes. Stable Diffusion XL 1.0 runs on Nvidia DGX Spark (128GB) at fp16 (~7.5 GB of ~112 GB usable).
How much VRAM does Stable Diffusion XL 1.0 need?
Nvidia DGX Spark (128GB) has room to spare. At fp16 the realistic peak is ~7.5 GB of VRAM, versus ~8.5 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~4 GB, much slower.
What do I use to run Stable Diffusion XL 1.0 locally?
Stable Diffusion XL 1.0 runs in ComfyUI or AUTOMATIC1111 / Forge (among others). It loads as a diffusion checkpoint plus its image encoder and VAE, not a single chat command.
Sources
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docs.nvidia.com · 2 sources
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github.com · 3 sources
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huggingface.co · 1 source
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nvidia.com · 1 source
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nvidianews.nvidia.com · 1 source
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ollama.com · 1 source
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stability.ai · 1 source
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tomshardware.com · 1 source
VRAM figures are sourced peak-usage anchors at the noted quant; catalog updated 2026-11-01. See methodology.