Yes, the RTX 5080 runs Stable Diffusion XL excellently. With 16GB GDDR7 VRAM, the RTX 5080 handles SDXL at full FP16 precision with room for ControlNet, refiner models, and batch generation. It is one of the best mid-range GPUs for serious image generation work.
The Short Answer
YES. SDXL in FP16 needs ~10.5GB peak, leaving 5.5GB free on the 16GB RTX 5080.
SDXL base in FP16 consumes approximately 6.5GB for model weights. During a 1024×1024 generation with 20 steps, peak VRAM usage including latents and attention maps reaches roughly 10.5GB. The RTX 5080 has ample room for this, plus space for add-ons like ControlNet (~2.5GB) or the SDXL refiner (~6GB with sequential loading). For a complete memory breakdown, see our Stable Diffusion VRAM requirements guide.
VRAM Analysis
| Configuration | VRAM Required | RTX 5080 (16GB) |
|---|---|---|
| SDXL Base FP16 (1024×1024) | ~10.5GB | Fits well |
| SDXL + ControlNet | ~13GB | Fits |
| SDXL + Refiner (sequential) | ~11GB | Fits |
| SDXL + ControlNet + Refiner | ~14GB | Tight fit |
| SDXL Batch Size 2 | ~14GB | Tight fit |
| SDXL Batch Size 4 | ~21GB | No |
Batch size 1 and 2 both work on the 5080. For larger batches or simultaneous loading of base, refiner, and ControlNet, you will need more VRAM. Sequential loading in ComfyUI handles this gracefully by swapping models in and out of VRAM as needed.
Performance Benchmarks
| GPU | SDXL 1024×1024 (20 steps) | Images per Minute |
|---|---|---|
| RTX 3050 (6GB) | ~12.5s | ~4.8 |
| RTX 4060 (8GB) | ~6.8s | ~8.8 |
| RTX 4060 Ti (16GB) | ~4.5s | ~13.3 |
| RTX 3090 (24GB) | ~2.9s | ~20.7 |
| RTX 5080 (16GB) | ~1.8s | ~33.3 |
| RTX 5090 (32GB) | ~1.2s | ~50.0 |
The RTX 5080 generates SDXL images at 1.8 seconds each, making it faster than the RTX 3090 by roughly 38%. For production image generation APIs, this throughput is excellent. Compare image model performance in our benchmarks page.
Setup Guide
ComfyUI provides the best SDXL experience with fine-grained control:
# Clone and set up ComfyUI
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
pip install -r requirements.txt
# Launch without lowvram flag (not needed on 16GB)
python main.py --listen 0.0.0.0 --port 8188Download the SDXL base model and place it in models/checkpoints/. The RTX 5080 does NOT need the --lowvram flag since SDXL fits comfortably in 16GB. Avoid enabling it, as it adds unnecessary model-swapping overhead.
For API-based generation, use the Automatic1111 backend:
python launch.py --xformers --api --listen --port 7860Recommended Alternative
If you need batch size 4+ or want to run SDXL alongside an LLM simultaneously, the RTX 3090 with 24GB gives more VRAM headroom, though the 5080 is faster clock-for-clock. For the ultimate SDXL setup, see our RTX 3090 SDXL + LLM guide.
For newer image models, check whether the RTX 5080 can run Flux.1. For LLM tasks on the same card, see the DeepSeek on 5080 analysis or the Whisper + LLM combo guide. Browse all GPU options on our dedicated GPU hosting page or in the GPU Comparisons category.
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