TensorFlow System Hardware Requirements

 

Windows

Category	Windows Requirements
CPU Requirements	Modern multi-core processor (Intel/AMD) with AVX support.
RAM (CPU Setup)	Minimum 8 GB (Recommended: 16 GB or more for large models).
GPU Requirements	NVIDIA GPU with CUDA support.
CUDA Version	CUDA 11.x or higher.
NVIDIA GPU Model	Compute Capability 3.5 or higher (e.g., GTX 10xx, RTX 20xx, RTX 30xx series).
CUDA Toolkit	Version 11.x or higher required.
cuDNN Version	cuDNN 8.x or later.
Recommended GPUs	RTX 3080 or higher (for deep learning). NVIDIA T4 or V100 (for enterprise workloads).
GPU Memory (VRAM)	Minimum 6 GB VRAM (Recommended: 8 GB or more).
Example GPU Setup	GPU: NVIDIA RTX 3080 (10 GB VRAM) CPU: Intel Core i7 or AMD Ryzen 7 RAM: 16 GB or higher Storage: 512 GB SSD or more
Software Requirements	CUDA Toolkit 11.x or higher cuDNN 8.x or higher NVIDIA Drivers Bazel (4.x or higher for source compilation)

macOS

Category	macOS Requirements
CPU Requirements	Apple Silicon (M1/M2/M3) or Intel processor with AVX support.
RAM (CPU Setup)	Minimum 8 GB (Recommended: 16 GB or more).
GPU Requirements	Apple Metal-supported GPUs (No official CUDA support on Mac).
CUDA Version	Not supported (Mac does not support CUDA).
NVIDIA GPU Model	macOS relies on Metal API for GPU acceleration.
CUDA Toolkit	Not applicable.
cuDNN Version	Not applicable.
Recommended GPUs	Apple M1/M2/M3 Neural Engine for AI acceleration.
GPU Memory (VRAM)	Unified memory, minimum 8 GB (Recommended: 16 GB or more).
Example GPU Setup	Apple M2 Max or Ultra RAM: 16 GB or higher Storage: 512 GB SSD or more
Software Requirements	Python 3.x TensorFlow Metal Plugin (for GPU acceleration on Apple devices)

Linux

Category	Linux Requirements
CPU Requirements	Modern multi-core processor (Intel/AMD) with AVX support.
RAM (CPU Setup)	Minimum 8 GB (Recommended: 16 GB or more).
GPU Requirements	NVIDIA GPU with CUDA support.
CUDA Version	CUDA 11.x or higher required for NVIDIA GPUs.
NVIDIA GPU Model	Compute Capability 3.5 or higher (e.g., GTX 10xx, RTX 20xx, RTX 30xx series).
CUDA Toolkit	CUDA 11.x or higher.
cuDNN Version	cuDNN 8.x or higher.
Recommended GPUs	RTX 3080 or higher for high-end deep learning. NVIDIA T4 or V100 for enterprise-level training.
GPU Memory (VRAM)	Minimum 6 GB VRAM (Recommended: 8 GB or more).
Example GPU Setup	GPU: NVIDIA RTX 3080 (10 GB VRAM) CPU: Intel Core i7 or AMD Ryzen 7 RAM: 16 GB or higher Storage: 512 GB SSD or more
Software Requirements	CUDA Toolkit 11.x or higher cuDNN 8.x or higher NVIDIA Drivers Bazel (4.x or higher for source compilation)

Notes:

• Windows and Linux require NVIDIA GPUs for CUDA-based acceleration, whereas macOS uses Metal API with Apple Silicon chips for AI tasks.
• On Linux, ensure you have the correct drivers for your NVIDIA GPU, and Linux distributions like Ubuntu 22.04 or later are highly recommended.

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Also Read:

• System Hardware Requirements for PyTorch in 2025
• System Hardware Requirements for Caffe in 2025
• System Requirements for Deep Learning in 2025
• GPU Hardware Requirement Guide for Llama 3 in 2025
• GPU Hardware Requirements Guide for DeepSeek Models in 2025