H200 vs RTX A4000
Detailed comparison of specifications, performance, and pricing between NVIDIA H200 SXM and NVIDIA RTX A4000
Difference Analysis
Full Specifications
| Specification | H200 | RTX A4000 | AMD Instinct MI100 |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | AMD |
| Series | Data Center | Workstation | Data Center |
| Architecture | Hopper | Ampere | CDNA |
| VRAM | 141GB | 16GB | 32GB |
| VRAM Type | HBM3e | GDDR6 | HBM2 |
| Memory Bandwidth | 4.8 TB/s | 448 GB/s | 1.2 TB/s |
| FP16 TFLOPS | 134.0 | 38.4 | 184.6 |
| Tensor TFLOPS | 2.0k | - | 184.6 |
| TDP | 700W | 140W | 300W |
| Form Factor | SXM | PCIe | - |
| Hardware Price | $$38k | $$900 | - |
| Cloud Price (min) | $2.30/hr | $0.060/hr | - |
Related Comparisons
H200 vs RTX A4000 FAQ
It depends on your use case. The H200 offers 5054% better performance (2.0k vs 38.4 TFLOPS). However, the RTX A4000 is 4122% cheaper. For raw performance, choose H200. For value, consider your budget and workload requirements.
The H200 has more VRAM with 141GB compared to 16GB (781% 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 16GB, the cheaper option may be more cost-effective.
The RTX A4000 is 4122% cheaper at $$900 vs $$38k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to H200 would give you 5054% more performance and 781% more VRAM. The upgrade cost difference is approximately $$37k. Consider if your workloads are bottlenecked by current GPU capabilities.