H100 vs A100 — Which GPU Is Worth It for LLM Inference?
H100 SXM costs $3.29/hr vs A100 80GB SXM at $2.49/hr — a 32% premium. H100 delivers ~3× the throughput on LLM inference. The break-even: if you're running at >50% GPU utilization and latency matters, H100 pays for itself.
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Frequently Asked Questions
How much faster is H100 than A100 for LLM inference?
H100 SXM has 3.35 TB/s memory bandwidth vs A100 SXM at 2.0 TB/s — a 1.7× difference. For LLM inference (which is memory-bandwidth bound), this translates to roughly 1.5–2× more tokens per second. Additionally, H100's NVLink 4.0 (900 GB/s vs 600 GB/s) enables faster multi-GPU tensor parallelism. Combined: 2–3× real-world throughput improvement for large models.
When should I use A100 instead of H100?
For models under 70B parameters where a single A100 80GB is sufficient: A100 is 32% cheaper with only 30% less throughput. The cost-per-token difference shrinks at lower model sizes. For 70B+ models requiring multiple GPUs, H100's NVLink advantage compounds significantly.
Data verified 2026-08-20. GPU rental prices change frequently — verify before purchasing. See methodology.