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image model · stable-diffusion · Linux

Can I run Stable Diffusion 1.5 on Nvidia DGX Spark (128GB)?

Compatibility verdict VRAM check
Yes, it runs fast on this GPU

Yes. Stable Diffusion 1.5 runs on Nvidia DGX Spark (128GB) at fp16 (~3.7 GB of ~112 GB usable).

Needs ~3.7 GB Device usable ~112 GB

Runs at fp16 using ~3.7 GB of ~112 GB usable.

Peak VRAM
~3.7 GB
Usable on device
~112 GB
Device memory
128 GB
Quant
fp16
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How to run it

Use AUTOMATIC1111 or ComfyUI 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.

Model stable-diffusion
Type
image (UNET)
Parameters
860M
Peak VRAM
~3.7 GB at fp16
Resolution
512×512
License
CreativeML OpenRAIL-M
Full Stable Diffusion 1.5 requirements →
Device Linux
Memory
128 GB unified
Usable for weights
~112 GB
Power draw
~140 W
Best runtime
llama.cpp (CUDA) / Ollama (CUDA)
Best models for Nvidia DGX Spark (128GB) →

You could also run

Run Stable Diffusion 1.5 on other hardware

Nvidia GeForce RTX 2060 (6GB)Apple M1 (8GB)iPhone 15 ProiPhone 16iPhone 16 ProiPhone 17

FAQ

Can Nvidia DGX Spark (128GB) run Stable Diffusion 1.5?

Yes. Stable Diffusion 1.5 runs on Nvidia DGX Spark (128GB) at fp16 (~3.7 GB of ~112 GB usable).

How much VRAM does Stable Diffusion 1.5 need?

Nvidia DGX Spark (128GB) has room to spare. At fp16 the realistic peak is ~3.7 GB of VRAM, versus ~4 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~2 GB, much slower.

What do I use to run Stable Diffusion 1.5 locally?

Stable Diffusion 1.5 runs in AUTOMATIC1111 or ComfyUI (among others). It loads as a diffusion checkpoint plus its image encoder and VAE, not a single chat command.

Sources

VRAM figures are sourced peak-usage anchors at the noted quant; catalog updated 2026-11-01. See methodology.