NVIDIA H100 vs NVIDIA A100
Specs, monthly cost in taka and the workloads each GPU suits, side by side.
Tensor figures are NVIDIA's published numbers with sparsity (dense is half). Source: H100, A100.
The short answer
Pick the NVIDIA H100 if: You train or fine-tune transformers seriously, want FP8, or run large-model inference where speed matters. It is the reference GPU most papers and tutorials assume.
Pick the NVIDIA A100 if: You fine-tune LLMs for a thesis or product, need 80 GB of fast HBM memory, or want a proven training GPU at a lower rate than the H100.
The NVIDIA H100 costs about 64% more per hour than the NVIDIA A100. If your model fits comfortably on the cheaper GPU and you are not short of time, the cheaper one usually wins. Compare with your own model →
Common questions
Which is faster, the NVIDIA H100 or the NVIDIA A100?
On paper the NVIDIA H100 is faster: 1,979 TFLOPS vs 624 TFLOPS FP16 tensor (with sparsity). Real-world speed depends on your model, batch size and memory bandwidth.
Which one costs less?
The NVIDIA A100 is ৳638 per hour and the NVIDIA H100 is ৳1,047, about 64% more. For 40 hours that is ৳25,520 vs ৳41,880.
Which has more memory?
Both have 80 GB.
Which should I choose for my project?
Choose the NVIDIA H100 if: You train or fine-tune transformers seriously, want FP8, or run large-model inference where speed matters. It is the reference GPU most papers and tutorials assume. Choose the NVIDIA A100 if: You fine-tune LLMs for a thesis or product, need 80 GB of fast HBM memory, or want a proven training GPU at a lower rate than the H100.