NVIDIA Tesla V100S VS AMD Radeon Pro V520
Choosing between **V100S** and **Radeon Pro V520** depends on your specific AI workload requirements. The **V100S** leads in both memory capacity and raw compute power, making it a stronger choice for high-end LLM training. Currently, you can rent these GPUs starting from **$0.88/h** and **$0.19/h** respectively across 2 providers.
Radeon Pro V520
📊 Detailed Specifications Comparison
| Specification | V100S | Radeon Pro V520 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Volta | RDNA 1 | - |
| Process Node | 12nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | Dual-slot PCIe | Single-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 32GB | 8GB | +300% |
| Memory Type | HBM2 | HBM2 | - |
| Memory Bandwidth | 1.1 TB/s | 512 GB/s | +121% |
| Memory Bus Width | 4096-bit | 2048-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 5,120 | N/A | |
| Stream Processors | N/A | 2,304 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 16.4 TFLOPS | 9.4 TFLOPS | +74% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 250W | 225W | +11% |
| PCIe Interface | PCIe 3.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA Tesla V100S
Higher VRAM capacity and memory bandwidth are critical for training large language models. The V100S offers 32GB compared to 8GB.
AI Inference
NVIDIA Tesla V100S
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
AMD Radeon Pro V520
Based on current cloud pricing, the Radeon Pro V520 starts at a lower hourly rate.
Technical Deep Dive: V100S vs Radeon Pro V520
This head-to-head pits NVIDIA's Volta against AMD's RDNA 1. The V100S has a significant **24GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **Radeon Pro V520** is currently about **78% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA Tesla V100S is Best For:
- HPC
- Scientific computing
- Legacy architectures
AMD Radeon Pro V520 is Best For:
- Cloud gaming
- Virtualization
- AI training
Frequently Asked Questions
Which GPU is better for AI training: V100S or Radeon Pro V520?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The V100S offers 32GB of HBM2 memory with 1.1 TB/s bandwidth, while the Radeon Pro V520 provides 8GB of HBM2 with 512 GB/s bandwidth. For larger models, the V100S's higher VRAM capacity gives it an advantage.
What is the price difference between V100S and Radeon Pro V520 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, V100S starts at $0.88/hour while Radeon Pro V520 starts at $0.19/hour. This represents a 363% price difference.
Can I use Radeon Pro V520 instead of V100S 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 V100S, the Radeon Pro V520 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the V100S's architecture may be essential.
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