NVIDIA T4G VS AMD Radeon Pro V520
Choosing between **T4G** and **Radeon Pro V520** depends on your specific AI workload requirements. While the **T4G** offers more VRAM for larger models, the **Radeon Pro V520** remains competitive in other areas. Currently, you can rent these GPUs starting from **$0.23/h** and **$0.19/h** respectively across 2 providers.
Radeon Pro V520
📊 Detailed Specifications Comparison
| Specification | T4G | Radeon Pro V520 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Turing | RDNA 1 | - |
| Process Node | 12nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | AWS Instance | Single-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 8GB | +100% |
| Memory Type | GDDR6 | HBM2 | - |
| Memory Bandwidth | 320 GB/s | 512 GB/s | -38% |
| Memory Bus Width | 256-bit | 2048-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 2,560 | N/A | |
| Stream Processors | N/A | 2,304 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 8.1 TFLOPS | 9.4 TFLOPS | -14% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 70W | 225W | -69% |
| PCIe Interface | PCIe 3.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA T4G
Higher VRAM capacity and memory bandwidth are critical for training large language models. The T4G offers 16GB compared to 8GB.
AI Inference
NVIDIA T4G
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: T4G vs Radeon Pro V520
This head-to-head pits NVIDIA's Turing against AMD's RDNA 1. The T4G has a significant **8GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **Radeon Pro V520** is currently about **17% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA T4G is Best For:
- ARM-based AI inference
- x86 native workloads
AMD Radeon Pro V520 is Best For:
- Cloud gaming
- Virtualization
- AI training
Frequently Asked Questions
Which GPU is better for AI training: T4G or Radeon Pro V520?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The T4G offers 16GB of GDDR6 memory with 320 GB/s bandwidth, while the Radeon Pro V520 provides 8GB of HBM2 with 512 GB/s bandwidth. For larger models, the T4G's higher VRAM capacity gives it an advantage.
What is the price difference between T4G and Radeon Pro V520 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, T4G starts at $0.23/hour while Radeon Pro V520 starts at $0.19/hour. This represents a 21% price difference.
Can I use Radeon Pro V520 instead of T4G 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 T4G, the Radeon Pro V520 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the T4G's architecture may be essential.
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