DeOldify Hardware Compatibility Guide

This guide outlines the supported hardware configurations for running DeOldify. We support a wide range of devices, from consumer GPUs to data center accelerators and CPUs.

🚀 Quick Reference Matrix

Hardware Type	Supported Devices	Recommended VRAM	Setup Guide
NVIDIA GPU	GeForce GTX 10-series+, RTX 20/30/40-series, Tesla, A100/H100	4GB+ (8GB+ for Video)	NVIDIA Setup
Intel GPU	Arc A-Series (A770, A750), Data Center GPU Flex/Max	8GB+	Intel Setup
CPU	Any modern x86_64 CPU (Intel/AMD)	N/A (System RAM > 16GB)	Standard Installation

🟢 NVIDIA GPUs (Recommended)

NVIDIA GPUs provide the most mature ecosystem for Deep Learning. DeOldify is optimized to take advantage of CUDA cores and Tensor cores on modern NVIDIA hardware.

Requirements

Driver: CUDA-compatible driver (ensure support for CUDA 11.8 or 12.x).
VRAM:
- Artistic Images: Minimum 4GB.
- Stable Video: Minimum 8GB recommended to handle frame buffering and larger batch sizes.
Performance: torch.backends.cudnn.benchmark is enabled by default to optimize performance on your specific card.

Legacy Support

We strive to support NVIDIA drivers released in the last 5 years. If you are on an older GPU (e.g., Maxwell/Pascal architecture) that does not support CUDA 12.x:

Ensure your driver supports at least CUDA 11.8.

Use the legacy environment file:

conda env create -f environment-legacy.yml
conda activate deoldify-legacy

🔵 Intel GPUs (New!)

We now support Intel's discrete GPUs, including the Arc A-Series and Data Center GPU Flex/Max series, via the Intel® Extension for PyTorch (IPEX).

Requirements

Hardware: Intel Arc A750, A770, or Data Center GPU Flex/Max Series.
Software: Intel® Graphics Driver (latest stable release).
Environment: Requires a specific Conda environment (see setup guide).

Performance Notes

XPU Acceleration: DeOldify automatically detects Intel GPUs as xpu devices.
Memory: Intel Arc cards with 16GB VRAM (like the A770 16GB) are excellent for high-resolution video colorization.

⚪ CPU (Fallback)

If no GPU is detected, DeOldify will fallback to CPU mode.

Pros & Cons

Pros: Works on almost any computer. No complex driver setup.
Cons: Significantly slower than GPU. Video colorization may be impractical for long clips.
Recommendation: Use for testing or single image colorization if no GPU is available.

📊 Benchmarks (Estimated)

Task	RTX 4090	Arc A770	CPU (Core i9)
Image (Artistic)	< 1 sec	~2 sec	~10-20 sec
Video (1 min, 1080p)	~2 mins	~4 mins	~30+ mins

Note: Benchmarks are approximate and depend on render factor and resolution.