H200 vs RTX 4090
Detailed comparison of specifications, performance, and pricing between NVIDIA H200 SXM and NVIDIA GeForce RTX 4090
Difference Analysis
Full Specifications
| Specification | H200 | RTX 4090 | RTX 3090 |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | NVIDIA |
| Series | Data Center | Consumer | Consumer |
| Architecture | Hopper | Ada Lovelace | Ampere |
| VRAM | 141GB | 24GB | 24GB |
| VRAM Type | HBM3e | GDDR6X | GDDR6X |
| Memory Bandwidth | 4.8 TB/s | 1.0 TB/s | 936 GB/s |
| FP16 TFLOPS | 134.0 | 165.2 | 71.2 |
| Tensor TFLOPS | 2.0k | - | - |
| TDP | 700W | 450W | 350W |
| Form Factor | SXM | PCIe | PCIe |
| Hardware Price | $$38k | $$1.8k | $$800 |
| Cloud Price (min) | $2.30/hr | $0.235/hr | $0.081/hr |
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H200 vs RTX 4090 FAQ
It depends on your use case. The H200 offers 1098% better performance (2.0k vs 165.2 TFLOPS). However, the RTX 4090 is 2011% cheaper. For raw performance, choose H200. For value, consider your budget and workload requirements.
The H200 has more VRAM with 141GB compared to 24GB (488% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the H200 is generally better due to its larger VRAM (141GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 24GB, the cheaper option may be more cost-effective.
The RTX 4090 is 2011% cheaper at $$1.8k vs $$38k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to H200 would give you 1098% more performance and 488% more VRAM. The upgrade cost difference is approximately $$36k. Consider if your workloads are bottlenecked by current GPU capabilities.