NVIDIA Tesla P100 VS AMD Radeon Pro V520
Choosing between **P100** and **Radeon Pro V520** depends on your specific AI workload requirements. While the **P100** offers more VRAM for larger models, the **Radeon Pro V520** remains competitive in other areas. Currently, you can rent these GPUs starting from **$0.08/h** and **$0.19/h** respectively across 7 providers.
Radeon Pro V520
📊 Detailed Specifications Comparison
| Specification | P100 | Radeon Pro V520 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Pascal | RDNA 1 | - |
| Process Node | 16nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | Dual-slot PCIe | Single-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 8GB | +100% |
| Memory Type | HBM2 | HBM2 | - |
| Memory Bandwidth | 732 GB/s | 512 GB/s | +43% |
| Memory Bus Width | 4096-bit | 2048-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 3,584 | N/A | |
| Stream Processors | N/A | 2,304 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 9.3 TFLOPS | 9.4 TFLOPS | -1% |
| 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 P100
Higher VRAM capacity and memory bandwidth are critical for training large language models. The P100 offers 16GB 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 P100
Based on current cloud pricing, the P100 starts at a lower hourly rate.
Technical Deep Dive: P100 vs Radeon Pro V520
This head-to-head pits NVIDIA's Pascal against AMD's RDNA 1. The P100 has a significant **8GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **P100** is currently about **58% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA Tesla P100 is Best For:
- Legacy AI workloads
- Precision-heavy training
AMD Radeon Pro V520 is Best For:
- Cloud gaming
- Virtualization
- AI training
Frequently Asked Questions
Which GPU is better for AI training: P100 or Radeon Pro V520?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The P100 offers 16GB of HBM2 memory with 732 GB/s bandwidth, while the Radeon Pro V520 provides 8GB of HBM2 with 512 GB/s bandwidth. For larger models, the P100's higher VRAM capacity gives it an advantage.
What is the price difference between P100 and Radeon Pro V520 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, P100 starts at $0.08/hour while Radeon Pro V520 starts at $0.19/hour. This represents a 58% price difference.
Can I use Radeon Pro V520 instead of P100 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 P100, the Radeon Pro V520 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the P100's architecture may be essential.
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