MI355X vs GB300
Detailed comparison of specifications, performance, and pricing between AMD Instinct MI355X and GB300
Difference Analysis
Full Specifications
| Specification | MI355X | GB300 | H100 PCIe |
|---|---|---|---|
| Brand | AMD | NVIDIA | NVIDIA |
| Series | Data Center | Data Center | Data Center |
| Architecture | CDNA4 | Blackwell | Hopper |
| VRAM | 288GB | 288GB | 80GB |
| VRAM Type | HBM3e | - | HBM2e |
| Memory Bandwidth | 8.0 TB/s | - | 2.0 TB/s |
| FP16 TFLOPS | - | - | 102.0 |
| Tensor TFLOPS | - | - | 1.5k |
| TDP | 500W | - | 350W |
| Form Factor | OAM | - | PCIe |
| Hardware Price | $$25k | - | $$28k |
| Cloud Price (min) | - | $8.62/hr | $2.89/hr |
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MI355X vs GB300 FAQ
It depends on your use case. The MI355X offers 0% better performance (- vs - TFLOPS). For raw performance, choose MI355X. For value, consider your budget and workload requirements.
The MI355X 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 MI355X 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 MI355X would give you 0% more performance and 0% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.
