Can NVIDIA GeForce RTX 5080 run FLUX.1 Dev?

12B parameter Image Gen model on 16GB GDDR7

Yes — runs at 8-bit quantization
~5.5-7.5 img/min
SpeedFast inference, near-native speed
QualityNear-lossless — virtually identical to FP16

VRAM Requirements

FLUX.1 Dev is a 12B parameter model. At full precision (FP16), it requires 32GB of VRAM. Your NVIDIA GeForce RTX 5080 has 16GB, so you'll need to quantize it to 8-bit (Q8) to fit.

FP16 (Full Precision)32GB (need 16GB more)

Maximum quality, no quantization

Q8 (8-bit)16GB (0GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)10GB (6GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 16GB GDDR7 at 960 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

FLUX.1 Dev at 8-bit precision on NVIDIA GeForce RTX 5080 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 FLUX.1 Dev weights from HuggingFace and place them in ComfyUI/models/. The model is approximately 32GB 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 5080 Specs

VRAM16GB GDDR7
Memory Bandwidth960 GB/s
TDP360W
CUDA Cores10,752
Street Price~$1150
AI Rating8/10

Other Image Gen Models on NVIDIA GeForce RTX 5080

About FLUX.1 Dev

State-of-the-art image generation. 16GB comfortable at FP8.

Category: Image Gen · Parameters: 12B · CUDA required: Recommended