H200 SXM5 vs A100 80GB
NVIDIA H200 SXM5 (Hopper, 141 GB) against NVIDIA A100 80GB (Ampere, 80 GB): memory, compute, power and rental price, compared for LLM inference and training.
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Side-by-Side Specifications
| Spec | H200 SXM5 | A100 80GB |
|---|---|---|
| Architecture | Hopper | Ampere |
| Memory | 141 GB HBM3e | 80 GB HBM2e |
| Memory bandwidth | 4,800 GB/s | 2,039 GB/s |
| FP16 tensor compute | 1,979 TFLOPS | 624 TFLOPS |
| INT8 tensor compute | 3,958 TOPS | 1,248 TOPS |
| Interconnect | NVLink 4.0 · 900 GB/s | NVLink 3.0 · 600 GB/s |
| TDP | 700 W | 400 W |
| Est. on-demand price | ~$10.00/h | ~$4.50/h |
| FP16 TFLOPS per $/h | 198 | 139 |
Highlighted values indicate the stronger spec. Hourly rates are indicative on-demand estimates.
Verdict
Raw performance: The H200 SXM5 leads on FP16 tensor compute (3.2x advantage), which translates directly into higher token throughput for inference and shorter training steps.
Memory: With 141 GB per card, the H200 SXM5 fits larger models on fewer GPUs — fewer cards means less inter-GPU communication and simpler deployments.
Value: At current on-demand rates, the H200 SXM5 delivers more compute per dollar (198 vs 139 FP16 TFLOPS per $/h). If your model fits in its VRAM budget, it is usually the more economical choice.
GPUs Needed for Popular LLMs
Cards required to serve each model at 8-bit quantization (with 20% overhead for activations and KV cache).
| Model | VRAM (8-bit) | H200 SXM5 | A100 80GB |
|---|---|---|---|
| GPT-5.6 Sol | 2682 GB | 20x | 34x |
| DeepSeek V4 Pro (671B) | 750 GB | 6x | 10x |
| Muse Spark 1.1 | 335 GB | 3x | 5x |
| Claude 5 Sonnet (175B) | 196 GB | 2x | 3x |
| Nova Premier (80B) | 89 GB | 1x | 2x |
| Nova Core (34B) | 38 GB | 1x | 1x |
| Nova Lite (12B) | 13 GB | 1x | 1x |
| Phi 3.5 (3.8B) | 4 GB | 1x | 1x |
Frequently Asked Questions
Which is better for LLM inference: H200 SXM5 or A100 80GB?
The H200 SXM5 delivers more raw FP16 compute (1,979 TFLOPS) and the H200 SXM5 offers the most memory per card (141 GB). For cost-efficiency, the H200 SXM5 currently gives more FP16 TFLOPS per dollar of on-demand rental (198 vs 139 TFLOPS per $/h).
How much more memory does the H200 SXM5 have?
The H200 SXM5 has 141 GB of HBM3e versus 80 GB of HBM2e for the A100 80GB — a ratio of 1.76x in favor of the H200 SXM5. More VRAM per card means fewer GPUs to fit a given model.
Is the H200 SXM5 or the A100 80GB cheaper to rent?
Estimated on-demand rates are ~$10.00/h for the H200 SXM5 and ~$4.50/h for the A100 80GB. Raw hourly price is only part of the story: normalize by throughput (TFLOPS per $/h) and by how many cards you need for your model's VRAM.
How do the H200 SXM5 and A100 80GB compare on power?
The H200 SXM5 has a TDP of 700W versus 400W for the A100 80GB. FP16 compute per watt: 2.8 vs 1.6 TFLOPS/W.
Deploy on a GPU cloud
Rent the H200 SXM5 or A100 80GB by the hour instead of buying hardware.
