NVIDIA T4G VS AMD Instinct MI250
Choosing between **T4G** and **Instinct MI250** depends on your specific AI workload requirements. The **Instinct MI250** 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 **$0.23/h** and **$1.30/h** respectively across 2 providers.
Instinct MI250
📊 Detailed Specifications Comparison
| Specification | T4G | Instinct MI250 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Turing | CDNA 2 | - |
| Process Node | 12nm | 6nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | AWS Instance | OAM | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 128GB | -88% |
| Memory Type | GDDR6 | HBM2e | - |
| Memory Bandwidth | 320 GB/s | 3.2 TB/s | -90% |
| Memory Bus Width | 256-bit | 8192-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 2,560 | N/A | |
| Stream Processors | N/A | 13,312 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 8.1 TFLOPS | 45.3 TFLOPS | -82% |
| FP64 (Double Precision) | N/A | 45.3 TFLOPS | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 70W | 500W | -86% |
| PCIe Interface | PCIe 3.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
AMD Instinct MI250
Higher VRAM capacity and memory bandwidth are critical for training large language models. The Instinct MI250 offers 128GB compared to 16GB.
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
NVIDIA T4G
Based on current cloud pricing, the T4G starts at a lower hourly rate.
Technical Deep Dive: T4G vs Instinct MI250
This head-to-head pits NVIDIA's Turing against AMD's CDNA 2. The Instinct MI250 has a significant **112GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **T4G** is currently about **82% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA T4G is Best For:
- ARM-based AI inference
- x86 native workloads
AMD Instinct MI250 is Best For:
- HPC
- Matrix math workloads
- CUDA native apps
Frequently Asked Questions
Which GPU is better for AI training: T4G or Instinct MI250?
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 Instinct MI250 provides 128GB of HBM2e with 3.2 TB/s bandwidth. For larger models, the Instinct MI250's higher VRAM capacity gives it an advantage.
What is the price difference between T4G and Instinct MI250 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, T4G starts at $0.23/hour while Instinct MI250 starts at $1.30/hour. This represents a 82% price difference.
Can I use Instinct MI250 instead of T4G for my workload?
It depends on your specific requirements. If your model fits within 128GB of VRAM and you don't need the additional throughput of the T4G, the Instinct MI250 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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