NVIDIA Tesla K80 VS AMD Radeon Pro V520

Choosing between **K80** and **Radeon Pro V520** depends on your specific AI workload requirements. While the **K80** offers more VRAM for larger models, the **Radeon Pro V520** remains competitive in other areas. Currently, you can rent these GPUs starting from **$0.10/h** and **$0.19/h** respectively across 3 providers.

NVIDIA

K80

VRAM 24GB
FP32 8.7 TFLOPS
TDP 300W
From $0.10/h 2 providers
AMD

Radeon Pro V520

VRAM 8GB
FP32 9.4 TFLOPS
TDP 225W
From $0.19/h 1 providers

📊 Detailed Specifications Comparison

Specification K80 Radeon Pro V520 Difference
Architecture & Design
Architecture Kepler RDNA 1 -
Process Node 28nm 7nm -
Target Market datacenter datacenter -
Form Factor Dual-slot PCIe Single-slot PCIe -
Memory & Bandwidth
VRAM Capacity 24GB 8GB +200%
Memory Type GDDR5 HBM2 -
Memory Bandwidth 480 GB/s 512 GB/s -6%
Memory Bus Width 384-bit 2048-bit -
Compute Infrastructure
CUDA Cores 4,992 N/A
Stream Processors N/A 2,304
AI & Compute Performance (TFLOPS)
FP32 (Single Precision) 8.7 TFLOPS 9.4 TFLOPS -7%
Power & Efficiency
TDP (Thermal Design Power) 300W 225W +33%
PCIe Interface PCIe 3.0 x16 PCIe 4.0 x16 -

🎯 Use Case Recommendations

🧠

LLM & Large Model Training

NVIDIA Tesla K80

Higher VRAM capacity and memory bandwidth are critical for training large language models. The K80 offers 24GB compared to 8GB.

AI Inference

AMD Radeon Pro V520

For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.

💰

Budget-Conscious Choice

NVIDIA Tesla K80

Based on current cloud pricing, the K80 starts at a lower hourly rate.

Automated Comparison

Technical Deep Dive: K80 vs Radeon Pro V520

This head-to-head pits NVIDIA's Kepler against AMD's RDNA 1. The K80 has a significant **16GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **K80** is currently about **47% cheaper** per hour, offering better value for budget-conscious projects.

NVIDIA Tesla K80 is Best For:

  • Old software support
  • Any modern AI

AMD Radeon Pro V520 is Best For:

  • Cloud gaming
  • Virtualization
  • AI training

Frequently Asked Questions

Which GPU is better for AI training: K80 or Radeon Pro V520?

For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The K80 offers 24GB of GDDR5 memory with 480 GB/s bandwidth, while the Radeon Pro V520 provides 8GB of HBM2 with 512 GB/s bandwidth. For larger models, the K80's higher VRAM capacity gives it an advantage.

What is the price difference between K80 and Radeon Pro V520 in the cloud?

Cloud GPU rental prices vary by provider and region. Based on our data, K80 starts at $0.10/hour while Radeon Pro V520 starts at $0.19/hour. This represents a 47% price difference.

Can I use Radeon Pro V520 instead of K80 for my workload?

It depends on your specific requirements. If your model fits within 8GB of VRAM and you don't need the additional throughput of the K80, the Radeon Pro V520 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the K80's architecture may be essential.

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