H100 PCIe vs RTX 4080 Super
Detailed comparison of specifications, performance, and pricing between NVIDIA H100 PCIe and NVIDIA GeForce RTX 4080 Super
Difference Analysis
Full Specifications
| Specification | H100 PCIe | RTX 4080 Super | AMD Radeon RX 7900 XT |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | AMD |
| Series | Data Center | Consumer | Consumer |
| Architecture | Hopper | Ada Lovelace | RDNA 3 |
| VRAM | 80GB | 16GB | 20GB |
| VRAM Type | HBM2e | GDDR6X | GDDR6 |
| Memory Bandwidth | 2.0 TB/s | 736 GB/s | 800 GB/s |
| FP16 TFLOPS | 102.0 | 104.4 | 104.0 |
| Tensor TFLOPS | 1.5k | - | - |
| TDP | 350W | 320W | 315W |
| Form Factor | PCIe | PCIe | - |
| Hardware Price | $$28k | $$1.1k | - |
| Cloud Price (min) | $2.39/hr | - | - |
Which Should You Choose?
For AI Training
Large model training needs maximum VRAM and memory bandwidth.
For AI Inference
Inference prioritizes throughput and cost efficiency.
On a Budget
Get the most capability for your money.
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H100 PCIe vs RTX 4080 Super FAQ
It depends on your use case. The H100 PCIe offers 1349% better performance (1.5k vs 104.4 TFLOPS). However, the RTX 4080 Super is 2567% cheaper. For raw performance, choose H100 PCIe. For value, consider your budget and workload requirements.
The H100 PCIe has more VRAM with 80GB compared to 16GB (400% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the H100 PCIe is generally better due to its larger VRAM (80GB). 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 4080 Super is 2567% cheaper at $$1.1k vs $$28k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to H100 PCIe would give you 1349% more performance and 400% more VRAM. The upgrade cost difference is approximately $$27k. Consider if your workloads are bottlenecked by current GPU capabilities.