--- title: "Rent H100 PCIE — $1.867/hr Cloud GPU Pricing (2026) | PowerGPU" description: "Rent the H100 PCIE (80 GB HBM2e) from $0.933/hr interruptible or $1.867/hr on-demand — fixed, ≥30% below market. 73 GPUs in 8 regions, per-second billing." url: https://powergpu.ai/gpu/h100-pcie last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Datacenter flagship · Hopper · launched 2022 · prices checked 2026-09-14 # Rent NVIDIA H100 PCIE — 80 GB, $1.867/hr on-demand - VRAM 80 GB HBM2e - FP16 tensor 756 TFLOPS - PowerScore 532 RTX 3090 = 100 - Configs 1–8× PCIe 5.0 - Online now 73 8 regions [On-demand (guaranteed) $1.867 /GPU-hr ≈ $1,363/mo · market ~~$2.67~~ (−30%)](https://cloud.powergpu.ai/?gpu=h100-pcie) [Interruptible $0.933 /GPU-hr flat −50% · pausable, disk kept](https://cloud.powergpu.ai/?gpu=h100-pcie&type=spot) [Reserved 3 mo $1.213 /GPU-hr −35% · capacity held for you](https://powergpu.ai/products/reserved) Billed per second, price locked at deploy. Storage $0.08/GB/mo · bandwidth $0.01/GB — [the whole fee schedule](https://powergpu.ai/pricing). Next weekly market re-check: 2026-09-21. Datacenter flagship · Hopper architecture The H100 PCIe is the Hopper card for standard servers: 80 GB HBM2e at 2 TB/s, 350 W and the FP8 Transformer Engine, with NVLink limited to bridged pairs. For single-GPU fine-tuning, quantized 70B inference and FP8 serving it delivers most of the SXM experience at a lower hourly rate — the value Hopper pick. This is training-grade silicon: HBM2e memory feeding tensor cores at multi-TB/s, NVLink for scaling past one card, and the reliability profile of Tier-III datacenter hosts. Teams rent it for pre-training, long fine-tunes and high-throughput inference where batch size is money. ## NVIDIA H100 PCIE specs: VRAM, TFLOPS, bandwidth - **GPU model**: NVIDIA H100 PCIE · **Architecture**: Hopper (2022) - **VRAM**: 80 GB HBM2e · **Memory bandwidth**: 2,000 GB/s - **FP16 tensor perf.**: 756 TFLOPS · **FP32 perf.**: 51.0 TFLOPS - **CUDA cores**: 14,592 · **TDP**: 350 W - **PowerScore ((RTX 3090 = 100))**: 532 · **PCIe generation**: Gen 5.0 - **Multi-GPU**: 1× – 8× · **Max instance storage**: 16,000 GB NVMe - **Network up to**: 10,000 Mbps · **CUDA**: 12.4 – 13.0 Bandwidth, CUDA cores, TDP and FP32 are public NVIDIA figures; FP16 tensor is the dense (non-sparsity) number. Machine-level values come from live inventory. ## H100 PCIE price per hour: on-demand, interruptible, reserved One public rule sets every price on this page: the marketplace median for the H100 PCIE ($2.67/hr, snapshot 2026-09-14) × 0.70, rounded down — so on-demand is $1.867, **30% below market**. Interruptible halves it; a 3-month reservation takes another 35% off. | Mode | Per GPU-hour | Per day (24 h) | Per month (730 h) | What you get | | --- | --- | --- | --- | --- | | **On-demand** | $1.867 | $44.81 | $1,363 | Guaranteed capacity, price locked at deploy, stop anytime | | **Interruptible** | $0.933 | $22.39 | $681 | Flat −50%; may pause under capacity pressure, disk kept, auto-requeue | | **Reserved (3 months)** | $1.213 | $29.11 | $885 | −35% on on-demand, rate locked for the term, capacity held | Per GPU: an 8× machine costs exactly 8× — no multi-GPU premium. Estimate a full month with storage and bandwidth in the [GPU cost calculator](https://powergpu.ai/calculator). ## What you can run on a H100 PCIE (80 GB VRAM) With 80 GB of HBM2e, a single card holds a **~32B-parameter LLM in FP16** or up to **~123B parameters quantized to 4-bit**, with room for KV-cache at practical context lengths. Scale to 8× GPUs on one machine for bigger models or bigger batches — the per-GPU price stays $1.867. - Recommended for [llm inference](https://powergpu.ai/use-cases/llm-inference) — Best $/token in class - Recommended for [fine-tuning](https://powergpu.ai/use-cases/fine-tuning) — QLoRA 70B on one GPU - Recommended for [video generation](https://powergpu.ai/use-cases/video-generation) — 32–141 GB VRAM on tap - One-click template: [vLLM on a H100 PCIE](https://powergpu.ai/templates/vllm) - One-click template: [PyTorch NGC on a H100 PCIE](https://powergpu.ai/templates/pytorch-ngc) - One-click template: [Axolotl — Fine Tuning on a H100 PCIE](https://powergpu.ai/templates/axolotl-fine-tuning) - Sizing help: [LLM VRAM requirements guide](https://powergpu.ai/guides/llm-vram-requirements) ## H100 PCIE availability by region 73 × H100 PCIE across 10 machines, live from inventory: - Seattle, WA - Stockholm - Tokyo - Mumbai - Chicago, IL - Frankfurt - Montréal - Los Angeles, CA ## H100 PCIE vs alternatives: price per TFLOP | GPU | VRAM | FP16 | On-demand | $ / TFLOP-hr | | --- | --- | --- | --- | --- | | **H100 PCIE** (this card) | 80 GB | 756 | $1.867 | $2.47‰ | | [H100 NVL](https://powergpu.ai/gpu/h100-nvl) | 80 GB | 835 | $1.811 | $2.17‰ | | [H200 NVL](https://powergpu.ai/gpu/h200-nvl) | 141 GB | 835 | $2.650 | $3.17‰ | | [A40](https://powergpu.ai/gpu/a40) | 48 GB | 144 | $0.765 | $5.31‰ | | [L40S](https://powergpu.ai/gpu/l40s) | 48 GB | 362 | $0.514 | $1.42‰ | ‰ = dollars per 1,000 TFLOP-hours of FP16 — a rough value-for-compute yardstick across cards. - [H100 SXM vs H100 PCIE](https://powergpu.ai/compare/h100-sxm-vs-h100-pcie) — specs, price per hour, which to rent - [H100 PCIE vs A100 PCIE](https://powergpu.ai/compare/h100-pcie-vs-a100-pcie) — specs, price per hour, which to rent - [L40S vs H100 PCIE](https://powergpu.ai/compare/l40s-vs-h100-pcie) — specs, price per hour, which to rent - [RTX PRO 6000 WS vs H100 PCIE](https://powergpu.ai/compare/rtx-pro-6000-ws-vs-h100-pcie) — specs, price per hour, which to rent - [All GPU comparisons](https://powergpu.ai/compare) ## Renting a H100 PCIE: frequently asked questions **How much does it cost to rent an NVIDIA H100 PCIE per hour?** $1.867 per GPU-hour on-demand — a fixed price set at least 30% below the current market median of $2.67. Interruptible capacity costs $0.933/hr and a 3-month reservation $1.213/hr. Around $1,363/month if you keep one running non-stop, billed per second. **What can a H100 PCIE with 80 GB VRAM run?** In LLM terms, roughly a 32B-parameter model in FP16 or up to ~123B parameters 4-bit quantized on a single card, with context headroom. Multi-GPU instances (up to 8× on current inventory) multiply that; diffusion and rendering workloads fit comfortably at this VRAM class. **Is the H100 PCIE available to rent right now?** Yes — 73 GPUs across 10 machines in 8 regions are listed as we render this page. Configurations go from 1× to 8×. Deploy from the console and it is running in about 30 seconds. **How do I deploy a H100 PCIE?** Create an account (email + password, no card, no KYC), top up in crypto, open the console, filter by H100 PCIE, pick a machine and a template such as PyTorch, vLLM or ComfyUI. The same deploy is one command with the CLI: powergpu launch --gpu h100-pcie --template pytorch. **Why is the H100 PCIE cheaper here than on GPU marketplaces?** We price from the public marketplace median and fix our on-demand rate at least 30% below it, rounded down. The price is re-checked weekly (next check 2026-09-21) and published — no auctions, no per-host roulette, no bidding. --- *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/gpu/h100-pcie · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt