Best GPU List

Best GPU for Stable Diffusion XL (SDXL) (2025)

SDXL generates stunning high-resolution images but is VRAM-hungry. While 8GB is the minimum, 16GB VRAM is highly recommended for faster generation and avoiding out-of-memory errors.

Minimum VRAM 8 GB
Recommended 16 GB+
BEST PERFORMANCE

GeForce RTX 5090

32GB GDDR7

The ultimate choice for Stable Diffusion XL (SDXL). With 32GB GDDR7 VRAM and a massive score of 14,480 , it handles large contexts and training with ease.

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BEST VALUE

Radeon RX 9060 XT 8 GB

8GB GDDR6

The smart choice. It meets the 8GB requirement perfectly while offering the best performance per dollar ratio.

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BUDGET PICK

GeForce RTX 3050 8 GB

8GB GDDR6

The most affordable way to run Stable Diffusion XL (SDXL). It hits the minimum specs needed to get started without breaking the bank.

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Why VRAM Matters for Stable Diffusion XL (SDXL)

SDXL operates at a native resolution of 1024x1024, which is 4x the pixel count of SD 1.5. This drastically increases VRAM usage during the VAE decode step and for storing the larger UNet. While 8GB cards can generate images using optimizations (like tiled VAE), they are slower and prone to crashing with LoRAs or ControlNet. 16GB VRAM allows for comfortable batch generation, training LoRAs, and using multiple ControlNets simultaneously.

Stable Diffusion XL (SDXL) GPU & System Requirements

CPU

Any modern quad-core CPU

RAM

16GB (32GB recommended for training)

Storage

Fast NVMe SSD (Crucial for loading models and saving images)

All Compatible GPUs for Stable Diffusion XL (SDXL)

GPUSteel Nomad ↓VRAM ↕Buy
GeForce RTX 509014,48032GB GDDR7Buy on Amazon
GeForce RTX 40909,23624GB GDDR6XBuy on Amazon
GeForce RTX 50808,76216GB GDDR7Buy on Amazon
Radeon RX 9070 XT7,24916GB GDDR6Buy on Amazon
Radeon RX 7900 XTX6,83724GB GDDR6Buy on Amazon

Frequently Asked Questions

What are the minimum GPU requirements for SDXL?

The minimum GPU requirement for SDXL is an NVIDIA card with 8GB VRAM. However, with 8GB, you will need to use optimizations like `--medvram` or tiled VAE, which slow down generation. 12GB or 16GB is recommended for a smooth experience.

Is RTX 4060 Ti 16GB good for SDXL?

Yes, it is an excellent budget choice for SDXL. While its memory bus is narrow, the 16GB buffer is the key feature that prevents crashes and allows for LoRA training, which 8GB cards struggle with.

AMD vs NVIDIA for Stable Diffusion?

NVIDIA is still the king due to CUDA and TensorRT optimization. AMD cards (via ROCm) are improving and offer better value per GB of VRAM, but NVIDIA offers the most stable and hassle-free experience with the widest compatibility (Automatic1111, ComfyUI).

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