NVIDIA H200 VS AMD Instinct MI355X
Choosing between **H200** and **Instinct MI355X** depends on your specific AI workload requirements. The **Instinct MI355X** 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 **$1.49/h** and **$2.29/h** respectively across 6 providers.
Instinct MI355X
📊 Detailed Specifications Comparison
| Specification | H200 | Instinct MI355X | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Hopper | CDNA 4 | - |
| Process Node | 4nm | 3nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM5 | OAM | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 141GB | 288GB | -51% |
| Memory Type | HBM3e | HBM3e | - |
| Memory Bandwidth | 4.8 TB/s | 8.0 TB/s | -40% |
| Memory Bus Width | 6144-bit | 8192-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 16,896 | N/A | |
| Tensor Cores (AI) | 528 | N/A | |
| Stream Processors | N/A | 24,576 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 67 TFLOPS | 210 TFLOPS | -68% |
| FP16 (Half Precision) | 1,979 TFLOPS | N/A | |
| TF32 (Tensor Float) | 989 TFLOPS | N/A | |
| FP64 (Double Precision) | 34 TFLOPS | N/A | |
| INT8 (Integer Precision) | 3,958 TOPS | N/A | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 700W | 1000W | -30% |
| PCIe Interface | PCIe 5.0 x16 | PCIe 5.0 x16 | - |
| Multi-GPU Interconnect | NVLink 4.0 (900 GB/s) | None | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA H200
Higher VRAM capacity and memory bandwidth are critical for training large language models. The Instinct MI355X offers 288GB compared to 141GB.
AI Inference
NVIDIA H200
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA H200
Based on current cloud pricing, the H200 starts at a lower hourly rate.
Technical Deep Dive: H200 vs Instinct MI355X
This head-to-head pits NVIDIA's Hopper against AMD's CDNA 4. The Instinct MI355X has a significant **147GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **H200** is currently about **35% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA H200 is Best For:
- LLM inference at scale
- Large context window models
- Budget deployments
AMD Instinct MI355X is Best For:
- Massive LLM training
- Budget projects
Frequently Asked Questions
Which GPU is better for AI training: H200 or Instinct MI355X?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The H200 offers 141GB of HBM3e memory with 4.8 TB/s bandwidth, while the Instinct MI355X provides 288GB of HBM3e with 8.0 TB/s bandwidth. For larger models, the Instinct MI355X's higher VRAM capacity gives it an advantage.
What is the price difference between H200 and Instinct MI355X in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, H200 starts at $1.49/hour while Instinct MI355X starts at $2.29/hour. This represents a 35% price difference.
Can I use Instinct MI355X instead of H200 for my workload?
It depends on your specific requirements. If your model fits within 288GB of VRAM and you don't need the additional throughput of the H200, the Instinct MI355X can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the H200's NVLink support (NVLink 4.0 (900 GB/s)) may be essential.
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