H100 PCIe vs L4
Detailed comparison of specifications, performance, and pricing between NVIDIA H100 PCIe and NVIDIA L4
Difference Analysis
Full Specifications
| Specification | H100 PCIe | L4 | AMD Instinct MI100 |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | AMD |
| Series | Data Center | Data Center | Data Center |
| Architecture | Hopper | Ada Lovelace | CDNA |
| VRAM | 80GB | 24GB | 32GB |
| VRAM Type | HBM2e | GDDR6 | HBM2 |
| Memory Bandwidth | 2.0 TB/s | 300 GB/s | 1.2 TB/s |
| FP16 TFLOPS | 102.0 | 60.6 | 184.6 |
| Tensor TFLOPS | 1.5k | 242.0 | 184.6 |
| TDP | 350W | 72W | 300W |
| Form Factor | PCIe | PCIe | - |
| Hardware Price | $$28k | $$2.8k | - |
| Cloud Price (min) | $2.39/hr | $0.390/hr | - |
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H100 PCIe vs L4 FAQ
It depends on your use case. The H100 PCIe offers 525% better performance (1.5k vs 242.0 TFLOPS). However, the L4 is 900% 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 24GB (233% 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 24GB, the cheaper option may be more cost-effective.
The L4 is 900% cheaper at $$2.8k vs $$28k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to H100 PCIe would give you 525% more performance and 233% more VRAM. The upgrade cost difference is approximately $$25k. Consider if your workloads are bottlenecked by current GPU capabilities.