GPUs/NVIDIA GeForce RTX 5070/Stable Diffusion 3.5 Large

Can NVIDIA GeForce RTX 5070 run Stable Diffusion 3.5 Large?

8B parameter Image Gen model on 12GB GDDR7

Yes — runs at 8-bit quantization
~6.1-8.4 img/min
SpeedFast inference, near-native speed
QualityNear-lossless — virtually identical to FP16

VRAM Requirements

Stable Diffusion 3.5 Large is a 8B parameter model. At full precision (FP16), it requires 18GB of VRAM. Your NVIDIA GeForce RTX 5070 has 12GB, so you'll need to quantize it to 8-bit (Q8) to fit.

FP16 (Full Precision)18GB (need 6GB more)

Maximum quality, no quantization

Q8 (8-bit)10GB (2GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)7GB (5GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 12GB GDDR7 at 672 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Stable Diffusion 3.5 Large at 8-bit precision on NVIDIA GeForce RTX 5070 produces images virtually identical to full precision. Generation speed is fast and you'll have some VRAM headroom for larger batch sizes or higher resolutions.

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 GeForce RTX 5070 Specs

VRAM12GB GDDR7
Memory Bandwidth672 GB/s
TDP250W
CUDA Cores6,144
Street Price~$620
AI Rating6/10

Other Image Gen Models on NVIDIA GeForce RTX 5070

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