GB300 vs MI355X
Detailed comparison of specifications, performance, and pricing between GB300 and AMD Instinct MI355X
Difference Analysis
Full Specifications
| Specification | GB300 | MI355X | H100 | H100 PCIe |
|---|---|---|---|---|
| Brand | NVIDIA | AMD | NVIDIA | NVIDIA |
| Series | Data Center | Data Center | Data Center | Data Center |
| Architecture | Blackwell | CDNA4 | Hopper | Hopper |
| VRAM | 288GB | 288GB | 80GB | 80GB |
| VRAM Type | - | HBM3e | HBM3 | HBM2e |
| Memory Bandwidth | - | 8.0 TB/s | 3.4 TB/s | 2.0 TB/s |
| FP16 TFLOPS | - | - | 134.0 | 102.0 |
| Tensor TFLOPS | - | - | 2.0k | 1.5k |
| TDP | - | 500W | 700W | 350W |
| Form Factor | - | OAM | SXM | PCIe |
| Hardware Price | - | $$25k | $$32k | $$28k |
| Cloud Price (min) | $8.62/hr | - | $1.47/hr | $2.89/hr |
Related Comparisons
GB300 vs MI355X FAQ
It depends on your use case. The GB300 offers 0% better performance (- vs - TFLOPS). For raw performance, choose GB300. For value, consider your budget and workload requirements.
The GB300 has more VRAM with 288GB compared to 288GB (0% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the GB300 is generally better due to its larger VRAM (288GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 288GB, the cheaper option may be more cost-effective.
Price comparison requires both GPUs to have available pricing data. Check individual GPU pages for current market prices.
Upgrading to GB300 would give you 0% more performance and 0% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.
