MI300 vs H200
Detailed comparison of specifications, performance, and pricing between AMD Instinct MI300 and H200
Difference Analysis
Full Specifications
| Specification | MI300 | H200 | H100 | H100 PCIe |
|---|---|---|---|---|
| Brand | AMD | NVIDIA | NVIDIA | NVIDIA |
| Series | Data Center | Data Center | Data Center | Data Center |
| Architecture | CDNA3 | Hopper | Hopper | Hopper |
| VRAM | 128GB | 141GB | 80GB | 80GB |
| VRAM Type | HBM3 | HBM3e | HBM3 | HBM2e |
| Memory Bandwidth | 5.3 TB/s | 4.8 TB/s | 3.4 TB/s | 2.0 TB/s |
| FP16 TFLOPS | 490.3 | 134.0 | 134.0 | 102.0 |
| Tensor TFLOPS | - | 2.0k | 2.0k | 1.5k |
| TDP | 750W | 700W | 700W | 350W |
| Form Factor | OAM | SXM | SXM | PCIe |
| Hardware Price | $$15k | $$38k | $$32k | $$28k |
| Cloud Price (min) | - | $2.30/hr | $1.47/hr | $2.89/hr |
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MI300 vs H200 FAQ
It depends on your use case. The H200 offers 304% better performance (2.0k vs 490.3 TFLOPS). However, the MI300 is 153% cheaper. For raw performance, choose H200. For value, consider your budget and workload requirements.
The H200 has more VRAM with 141GB compared to 128GB (10% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the H200 is generally better due to its larger VRAM (141GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 128GB, the cheaper option may be more cost-effective.
The MI300 is 153% cheaper at $$15k vs $$38k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
The H200 actually offers 304% better performance. An "upgrade" to MI300 would be a downgrade in raw performance, though it may offer other benefits like lower power consumption or cost.
