---
title: "H100 SXM vs A100 SXM4: Specs & Price per Hour (2026) | PowerGPU"
description: "H100 SXM vs A100 SXM4: 80 vs 80 GB VRAM, 990 vs 312 FP16 TFLOPS, $1.428 vs $0.560/hr on PowerGPU. Specs side by side, live rental prices, which to rent."
url: https://powergpu.ai/compare/h100-sxm-vs-a100-sxm4
last_modified: 2026-09-14T11:04:20+00:00
prices_as_of: 2026-09-14
site: PowerGPU (powergpu.ai)
---

Compare · prices checked 2026-09-14

# H100 SXM vs A100 SXM4: specs, price per hour, which to rent

NVIDIA H100 SXM (80 GB, **$1.428** /hr) against NVIDIA A100 SXM4 (80 GB, **$0.560** /hr): public specs side by side, live fixed prices from our sheet, what fits in each card's VRAM, and a verdict written for real workloads — both are rentable right now.

- [NVIDIA H100 SXM Hopper · 80 GB HBM3 · 990 FP16 TFLOPS · $1.428/hr on-demand · $0.714/hr interruptible · 54 online](https://powergpu.ai/gpu/h100-sxm)
- [NVIDIA A100 SXM4 Ampere · 80 GB HBM2e · 312 FP16 TFLOPS · $0.560/hr on-demand · $0.280/hr interruptible · 95 online](https://powergpu.ai/gpu/a100-sxm4)

## H100 SXM vs A100 SXM4 specifications

Public NVIDIA figures (dense, non-sparsity). The last column is H100 SXM relative to A100 SXM4.

| Spec | H100 SXM | A100 SXM4 | Difference |
| --- | --- | --- | --- |
| Architecture | Hopper (2022) | Ampere (2020) | — |
| VRAM | 80 GB HBM3 | 80 GB HBM2e | same |
| Memory bandwidth | 3,350 GB/s | 2,039 GB/s | +64% |
| FP16 tensor (dense) | 990 TFLOPS | 312 TFLOPS | +217% |
| FP32 | 67.0 TFLOPS | 19.5 TFLOPS | +244% |
| CUDA cores | 16,896 | 6,912 | +144% |
| TDP | 700 W | 400 W | +75% |
| PCIe · NVLink | Gen 5.0 · NVLink | Gen 4.0 · NVLink | — |
| PowerScore (RTX 3090 = 100) | 697 | 220 | +217% |
| Max GPUs per machine | 8× | 8× | — |

## H100 SXM vs A100 SXM4 price per hour

Fixed rates from our sheet — every on-demand price is the marketplace median × 0.70, rounded down. Monthly = 730 hours.

| Rate | H100 SXM | A100 SXM4 | Cheaper |
| --- | --- | --- | --- |
| On-demand, per GPU-hour | $1.428 | $0.560 | A100 SXM4 (−61%) |
| Interruptible, per GPU-hour | $0.714 | $0.280 | A100 SXM4 |
| Reserved (3 mo), per GPU-hour | $0.928 | $0.364 | A100 SXM4 |
| On-demand, per month | $1,042 | $409 | A100 SXM4 |
| Market median (reference) | $2.04 | $0.80 | — |
| $ per 1,000 FP16 TFLOP-hours | $1.44 | $1.79 | H100 SXM (better value) |
| $ per GB of VRAM per hour | $0.0178 | $0.0070 | A100 SXM4 (better value) |

Try a full month with storage and bandwidth in the [GPU cost calculator](https://powergpu.ai/calculator).

## What fits in VRAM: 80 GB vs 80 GB

| Workload | H100 SXM | A100 SXM4 |
| --- | --- | --- |
| Largest LLM in FP16, one card | ~32B | ~32B |
| Largest LLM at 4-bit, one card | ~123B | ~123B |
| Flux dev (FP8, ~17 GB) | fits | fits |
| Wan 2.x 14B video (offloaded) | yes | yes |
| 70B 4-bit LLM on one card | yes | yes |

Rules of thumb: ~2.4 GB per billion parameters in FP16 all-in, ~0.62 GB in 4-bit. Full tables in the [VRAM guide](https://powergpu.ai/guides/llm-vram-requirements).

## Verdict: which should you rent?

The H100 SXM trains transformers roughly 2–3× faster than the A100 SXM4 thanks to FP8 and 3.35 TB/s of HBM3; the A100 costs far less per hour and still wins dollars per step for ≤13B models, LoRA farms and FP64 HPC. Rent the H100 for deadlines and FP8 serving, the A100 for volume experiments.

- **Cheaper per hour:** A100 SXM4 ($0.560 vs $1.428, −61%).
- **More VRAM:** H100 SXM (80 GB vs 80 GB).
- **More FP16 throughput:** H100 SXM (about 3.2×).
- **Best value per TFLOP-hour:** H100 SXM.
- **Best value per GB of VRAM:** A100 SXM4.
- **Multi-GPU:** H100 SXM with NVLink · A100 SXM4 with NVLink.

## Related comparisons

[All comparisons](https://powergpu.ai/compare)

- [H100 SXM vs H200 $1.428 vs $2.791 per hour](https://powergpu.ai/compare/h100-sxm-vs-h200)
- [H100 SXM vs B200 $1.428 vs $5.425 per hour](https://powergpu.ai/compare/h100-sxm-vs-b200)
- [H100 SXM vs H100 PCIE $1.428 vs $1.867 per hour](https://powergpu.ai/compare/h100-sxm-vs-h100-pcie)
- [A100 SXM4 vs A100 PCIE $0.560 vs $0.374 per hour](https://powergpu.ai/compare/a100-sxm4-vs-a100-pcie)
- [RTX 5090 vs A100 SXM4 $0.439 vs $0.560 per hour](https://powergpu.ai/compare/rtx-5090-vs-a100-sxm4)
- [H100 NVL vs H100 SXM $1.811 vs $1.428 per hour](https://powergpu.ai/compare/h100-nvl-vs-h100-sxm)

## H100 SXM vs A100 SXM4: FAQ

Deeper reading: [H100 vs H200 vs B200](https://powergpu.ai/guides/h100-vs-h200-vs-b200), [RTX 4090 vs RTX 5090](https://powergpu.ai/guides/rtx-4090-vs-rtx-5090), [how cloud GPU pricing works](https://powergpu.ai/guides/cloud-gpu-pricing-explained).

**Is the H100 SXM faster than the A100 SXM4?**

On dense FP16 tensor throughput the H100 SXM leads by about 3.2× (990 vs 312 TFLOPS). Memory bandwidth matters as much for inference: H100 SXM 3,350 GB/s vs A100 SXM4 2,039 GB/s.

**Which is cheaper to rent, the H100 SXM or the A100 SXM4?**

The A100 SXM4: $0.560/hr on-demand versus $1.428/hr — 61% less. Interruptible rates are $0.714 (H100 SXM) and $0.280 (A100 SXM4). Per TFLOP-hour the better value is the H100 SXM.

**Which has more VRAM and what does that change?**

The H100 SXM has 80 GB versus 80 GB. In LLM terms that is roughly a 32B FP16 model (or ~123B in 4-bit) on one card against 32B FP16 (~123B 4-bit). If the model does not fit, speed is irrelevant.

**Can I rent both on PowerGPU right now?**

Yes — 54 × H100 SXM and 95 × A100 SXM4 are online as this page renders, deployable in about 30 seconds, billed per second, paid in crypto with no KYC.

---

*About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API.

Source: https://powergpu.ai/compare/h100-sxm-vs-a100-sxm4 · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt