NVIDIA A30 Vs T4 Vs V100 Vs A100 Vs RTX 8000 GPU Cards

When it comes to GPU cards, NVIDIA offers a wide range of options tailored for various applications and performance requirements. Let's compare some of the popular GPU cards from NVIDIA: A30, T4, V100, A100, and RTX 8000.

NVIDIA A30 GPU

The NVIDIA A30 is designed for mainstream AI and data analytics workloads. It features 24 GB of GDDR6 memory and 6848 CUDA cores, making it suitable for tasks such as deep learning inference, data analytics, and virtual desktop infrastructure (VDI).

NVIDIA T4 GPU

The NVIDIA T4 is a versatile GPU optimized for AI inference, deep learning training, and virtual desktops. It comes with 16 GB of GDDR6 memory and 320 Tensor Cores, offering efficient performance for a wide range of machine learning tasks.

NVIDIA V100 GPU

The NVIDIA V100 is a flagship GPU renowned for its performance in AI and scientific computing. It boasts up to 32 GB of HBM2 memory and 5120 CUDA cores, delivering unparalleled compute power for deep learning training, inference, and high-performance computing (HPC) applications.

NVIDIA A100 GPU

The NVIDIA A100 is NVIDIA's most advanced GPU, built on the Ampere architecture. With up to 80 GB of HBM2 memory and 6912 CUDA cores, the A100 is optimized for AI training and inference, offering groundbreaking performance for deep learning workloads.

NVIDIA RTX 8000 GPU

The NVIDIA RTX 8000 is a professional-grade GPU designed for demanding visualization and rendering tasks. It features 48 GB of GDDR6 memory and 4608 CUDA cores, providing exceptional performance for applications such as computer-aided design (CAD), scientific visualization, and virtual reality (VR) content creation.

Comparison Table

GPU Card	Memory	CUDA Cores	Tensor Cores	Memory Bandwidth	Peak Half Precision (FP16) Performance	Peak Single Precision (FP32) Performance	Optimized For
NVIDIA A30	24 GB GDDR6	6848	N/A	624 GB/s	53.2 TFLOPS	26.6 TFLOPS	Mainstream AI, Data Analytics
NVIDIA T4	16 GB GDDR6	320	320	320 GB/s	8.1 TFLOPS	8.1 TFLOPS	AI Inference, Deep Learning Training
NVIDIA V100	32 GB HBM2	5120	N/A	900 GB/s	125 TFLOPS	15.7 TFLOPS	Deep Learning Training, Inference, HPC
NVIDIA A100	Up to 80 GB HBM2	6912	N/A	1.6 TB/s	312 TFLOPS	19.5 TFLOPS	AI Training, Inference
NVIDIA RTX 8000	48 GB GDDR6	4608	N/A	624 GB/s	63.8 TFLOPS	10.1 TFLOPS	Visualization, Rendering

Conclusion

The comparison table provides an overview of the key specifications and performance metrics of NVIDIA A30, T4, V100, A100, and RTX 8000 GPU cards. Depending on the specific requirements of your workload, you can choose the GPU card that offers the optimal balance of memory capacity, compute power, and specialized features.