NVIDIA B100 VS AMD Instinct MI300X
Choosing between **B100** and **Instinct MI300X** depends on your specific AI workload requirements. Currently, you can rent these GPUs starting from **$0.00/h** and **$0.95/h** respectively across 6 providers.
Instinct MI300X
📊 Detailed Specifications Comparison
| Specification | B100 | Instinct MI300X | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Blackwell | CDNA 3 | - |
| Process Node | 4nm | 5nm + 6nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM | OAM | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 192GB | 192GB | |
| Memory Type | HBM3e | HBM3 | - |
| Memory Bandwidth | 8.0 TB/s | 5.3 TB/s | +51% |
| Memory Bus Width | 8192-bit | 8192-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 14,336 | N/A | |
| Tensor Cores (AI) | 448 | N/A | |
| Stream Processors | N/A | 19,456 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 70 TFLOPS | 163.4 TFLOPS | -57% |
| FP16 (Half Precision) | 3,500 TFLOPS | 1,307.4 TFLOPS | +168% |
| TF32 (Tensor Float) | 1,750 TFLOPS | N/A | |
| FP64 (Double Precision) | 35 TFLOPS | 81.7 TFLOPS | -57% |
| INT8 (Integer Precision) | 7,000 TOPS | 2,614.9 TOPS | +168% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 700W | 750W | -7% |
| PCIe Interface | PCIe 5.0 x16 | PCIe 5.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA B100
Higher VRAM capacity and memory bandwidth are critical for training large language models. The Instinct MI300X offers 192GB compared to 192GB.
AI Inference
NVIDIA B100
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
AMD Instinct MI300X
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: B100 vs Instinct MI300X
This head-to-head pits NVIDIA's Blackwell against AMD's CDNA 3.
NVIDIA B100 is Best For:
- Large-scale AI training
- Budget deployments
AMD Instinct MI300X is Best For:
- LLM inference at scale
- Large VRAM capacity
- CUDA-only software
Frequently Asked Questions
Which GPU is better for AI training: B100 or Instinct MI300X?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The B100 offers 192GB of HBM3e memory with 8.0 TB/s bandwidth, while the Instinct MI300X provides 192GB of HBM3 with 5.3 TB/s bandwidth. Both GPUs have similar VRAM capacity, so performance characteristics become the deciding factor.
What is the price difference between B100 and Instinct MI300X in the cloud?
Cloud GPU rental prices vary by provider and region. Check our price tracker for the latest rates from 50+ cloud providers.
Can I use Instinct MI300X instead of B100 for my workload?
It depends on your specific requirements. If your model fits within 192GB of VRAM and you don't need the additional throughput of the B100, the Instinct MI300X can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the B100's architecture may be essential.
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