AMD Instinct MI250 VS NVIDIA A100 80GB
Choosing between **Instinct MI250** and **A100 80GB** 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 **$1.30/h** and **$0.40/h** respectively across 42 providers.
Instinct MI250
A100 80GB
📊 Detailed Specifications Comparison
| Specification | Instinct MI250 | A100 80GB | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | CDNA 2 | Ampere | - |
| Process Node | 6nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | OAM | SXM4 / PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 128GB | 80GB | +60% |
| Memory Type | HBM2e | HBM2e | - |
| Memory Bandwidth | 3.2 TB/s | 2.0 TB/s | +57% |
| Memory Bus Width | 8192-bit | 5120-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | N/A | 6,912 | |
| Tensor Cores (AI) | N/A | 432 | |
| Stream Processors | 13,312 | N/A | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 45.3 TFLOPS | 19.5 TFLOPS | +132% |
| FP16 (Half Precision) | N/A | 312 TFLOPS | |
| TF32 (Tensor Float) | N/A | 156 TFLOPS | |
| FP64 (Double Precision) | 45.3 TFLOPS | 9.7 TFLOPS | +367% |
| INT8 (Integer Precision) | N/A | 624 TOPS | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 500W | 400W | +25% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
| Multi-GPU Interconnect | None | NVLink 3.0 (600 GB/s) | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA A100 80GB
Higher VRAM capacity and memory bandwidth are critical for training large language models. The Instinct MI250 offers 128GB compared to 80GB.
AI Inference
NVIDIA A100 80GB
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA A100 80GB
Based on current cloud pricing, the A100 80GB starts at a lower hourly rate.
Technical Deep Dive: Instinct MI250 vs A100 80GB
This head-to-head pits AMD's CDNA 2 against NVIDIA's Ampere. The Instinct MI250 has a significant **48GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **A100 80GB** is currently about **69% cheaper** per hour, offering better value for budget-conscious projects.
AMD Instinct MI250 is Best For:
- HPC
- Matrix math workloads
- CUDA native apps
NVIDIA A100 80GB is Best For:
- AI model training
- Scientific computing
- Newest FP8 precision workloads
Frequently Asked Questions
Which GPU is better for AI training: Instinct MI250 or A100 80GB?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The Instinct MI250 offers 128GB of HBM2e memory with 3.2 TB/s bandwidth, while the A100 80GB provides 80GB of HBM2e with 2.0 TB/s bandwidth. For larger models, the Instinct MI250's higher VRAM capacity gives it an advantage.
What is the price difference between Instinct MI250 and A100 80GB in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, Instinct MI250 starts at $1.30/hour while A100 80GB starts at $0.40/hour. This represents a 225% price difference.
Can I use A100 80GB instead of Instinct MI250 for my workload?
It depends on your specific requirements. If your model fits within 80GB of VRAM and you don't need the additional throughput of the Instinct MI250, the A100 80GB can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the Instinct MI250's architecture may be essential.
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