GPUs/NVIDIA A100 40GB/Stable Diffusion 3.5 Large

Can NVIDIA A100 40GB run Stable Diffusion 3.5 Large?

8B parameter Image Gen model on 40GB HBM2e

Yes — runs at full precision
~8.1-11.1 img/min
SpeedFastest possible inference
QualityMaximum quality, no degradation

VRAM Requirements

Stable Diffusion 3.5 Large is a 8B parameter model. At full precision (FP16), it requires 18GB of VRAM. Your NVIDIA A100 40GB has 40GB — enough to run it without any quantization.

FP16 (Full Precision)18GB (22GB free)

Maximum quality, no quantization

Q8 (8-bit)10GB (30GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)7GB (33GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 40GB HBM2e at 1555 GB/s bandwidth
Recommended system RAM: 80GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

NVIDIA A100 40GB runs Stable Diffusion 3.5 Large at full precision with room to spare. You can generate high-resolution images, use complex prompts, and batch multiple generations. Expect fast generation times at 1024x1024 and above.

How to Set It Up

Step 1: Install ComfyUI

git clone https://github.com/comfyanonymous/ComfyUI.git && cd ComfyUI && pip install -r requirements.txt

ComfyUI is the recommended UI for Stable Diffusion and FLUX models.

Step 2: Download the model

Download Stable Diffusion 3.5 Large weights from HuggingFace and place them in ComfyUI/models/. The model is approximately 18GB at full precision.

Step 3: Launch and generate

python main.py

Open http://localhost:8188 in your browser. You can use the full precision weights.

NVIDIA A100 40GB Specs

VRAM40GB HBM2e
Memory Bandwidth1555 GB/s
TDP250W
CUDA Cores6,912
Street Price~$4500
AI Rating10/10

Other Image Gen Models on NVIDIA A100 40GB

About Stable Diffusion 3.5 Large

Latest SD architecture. Better quality than SDXL, slightly more VRAM hungry.

Category: Image Gen · Parameters: 8B · CUDA required: Recommended