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H100 NVL

Overview

H100 NVL It is the China-market variant of the NVIDIA H100 PCIe dual-slot Air-cooled form factor : 94GB HBM3 memory per card, 3,341 TFLOPS FP8, 60 TFLOPS FP64 Tensor, configurable 350-400W TDP, NVLink bridging at 600GB/s (2/4-way) — no HGX baseboard system required and plugs directly into a standard x86 server (official spec snapshot basis [1]).

How it relates to the HGX H100 baseboard version (SXM): same die, different form factor — the NVL version is a PCIe dual-slot Air-cooled card, while the HGX baseboard version is an SXM Liquid-cooled/Air-cooled system (8 GPUs fully interconnected via NVLink). For buyers: PCIe deployment has a lower barrier — no baseboard system needed; plugs straight into standard x86 servers. The 94GB memory is a 17.5% increase over the H100 PCIe's 80GB.

Comparison with the H200 NVL: memory 94GB vs 141GB (-33%), bandwidth 3.9TB/s vs 4.8TB/s, FP8 identical at 3,341 TFLOPS — the H200 NVL is the direct memory upgrade of the H100 NVL (official comparison basis [1]). This entry carries no market pricing — actual price subject to the seller's quote.

Use Cases

AIXX Index (0–100): Estimated in this Pedia via weighted public specs — memory 40% + interconnect 30% + ecosystem 30%.

History

In 2023 , H100 NVL launch: the Hopper-generation PCIe inference flagship — 94GB HBM3 memory, a 17.5% uplift over the H100 PCIe's 80GB, with FP8 Tensor Core at 3,341 TFLOPS in the same class (official spec snapshot basis [1]).

2024–2025 , inference at scale: explosive demand for online LLM inference — plug-and-play PCIe plus 94GB of memory made the H100 NVL one of the volume mainstays on the inference side (per this database's compilation).

2025-2026 , Blackwell takes over: RTX PRO 6000 Blackwell and the B200/B300 series launch — the H100 NVL moves into stock and parallel circulation (per this database's compilation). Cross-border trade policy is still evolving; this database reflects public reporting and does not constitute legal advice.

Technical Specifications

Item Specs (H100 NVL · official figures)
Architecture NVIDIA Hopper
Board Memory 94GB HBM3
Memory Bandwidth 3.9TB/s
FP8 / INT8 3,341 TFLOPS / 3,341 TOPS
FP16 1,671 TFLOPS
FP64 / FP64 Tensor 30 / 60 TFLOPS
FP32 60 TFLOPS
Interconnect NVLink 600GB/s
Codecs 7 NVDEC
Power 350-400W (configurable)
Form Factor PCIe dual-slot Air-cooled
MIG Up to 7 instances @ 12GB

Specifications per NVIDIA official snapshot (October 2026 basis [1], verified line-by-line against the Spec Card).

Three form factors of the H100 family

Item H100 NVL(PCIe) HGX H100 8-GPU (SXM) H200 NVL(PCIe)
Memory 94GB HBM3 80GB HBM3 × 8 141GB HBM3e
Interconnect NVLink bridging at 600GB/s NVLink 900GB/s all-to-all NVLink bridging at 900GB/s
FP8 3,341 TFLOPS 3,358 TFLOPS 3,341 TFLOPS
Power 350-400W 700W (configurable) 600W (configurable)
One-line buying advice Inference / single-server direct install Large-scale training clusters High-memory inference upgrade

Family Members

The H100 family is tiered by form factor; the NVL version is the PCIe inference flagship:

Cooling & Deployment

The H100 NVL is a PCIe dual-slot Air-cooled card (350-400W configurable) — plugs straight into standard x86 servers, no HGX baseboard system required (official spec snapshot basis [1]). Deployment quick-reference: Power (the 400W tier needs an adequate PSU and 16-pin CEM5 power cables), PCIe Gen5 direct attach (x16 direct to CPU, avoid switches that eat bandwidth), airflow (a 400W Full Load dual-slot card puts more airflow pressure than the 300W class — watch intake temperatures).

Multi-GPU deployment: 2-GPU NVLink bridging delivers 600GB/s of interconnect — inference throughput scaling doesn't require an HGX baseboard. 4-GPU bridging scales further but needs a dedicated bridge kit. Density: 2-4 GPUs per 2U server is common (airflow pressure from 400W×4=1.6kW needs careful planning).

Model Compatibility

Model / Scenario Memory requirements (FP16 estimates) H100 NVL deployment scenarios AIXX Index
70B-class inference (INT8) ~70GB 94GB per card with ample headroom + MIG partitioning for multi-tenant 88
13B-class inference (FP16) ~26GB Single card easily + MIG partitioning for multiple instances 90
Long-context inference KV cache scales linearly with length 94GB offers more KV cache room than the 80GB bridge 84
Large model training — PCIe interconnect limitation — for large-scale training, look at the HGX SXM series 62

Gallery

Software & Ecosystem

Item Requirements / Status
CUDA Hopper generation (Compute Capability 9.0) — supported since CUDA 11.8
Frameworks Full support across PyTorch / TensorFlow / vLLM / TensorRT
MIG Up to 7 instances @ 12GB
Driver NVIDIA data center driver line (shared with the HGX H100)

Purchasing & Inspection

H100 NVL procurement inspection points (three items):1Memory capacity verification94GB HBM3 — verify with nvidia-smi; the price gap between 94GB and 80GB is large, and mislabeling is a common risk.2MIG partitioning testTest the 7-instance partitioning — the core acceptance item for multi-tenant inference.3Codec testTest concurrent 7×NVDEC transcoding — the core acceptance metric for video workloads.Acceptance Quick Reference QUICK CHECKH100 NVL four-step quick check:1Identitynvidia-smi: H100 NVL model, 94GB memory, ECC status — match each item against the contract.2Full-load Burn-in Test400W tier Full Load: stable temperatures, zero ECC errors (per the case-law framework).3FP8 computeFP8 benchmark test (≥80% counts as Pass, estimated figures) — the real throughput anchor for inference production lines.4MIG partitioningTest the 7-instance partitioning — the core acceptance item for multi-tenant scenarios.Shipping & Delivery LOGISTICS1Cross-border complianceThe H100 NVL's export-control status toward China mirrors the H100 — consult professional counsel for cross-border procurement compliance; this database does not constitute legal advice.Glossary Cards GLOSSARYNVL namingIn NVIDIA's product lineup, the NVL suffix = a PCIe card with NVLink bridging — the H100 NVL achieves 600GB/s GPU-to-GPU Interconnect via 2/4-way NVLink bridging (not the SXM baseboard all-to-all).

H100 NVL memory specs: 94GB HBM3 (up 17.5% from the H100 PCIe's 80GB HBM2e), 3.9TB/s bandwidth — a significant lift of the memory ceiling for LLM inference in a PCIe form factor.

NVLink Bridge: physical bridging hardware between 2 or 4 GPUs — bypassing PCIe Switches, connecting card-to-card directly over NVLink. The H100 NVL's bridge bandwidth is 600GB/s (versus 900GB/s all-to-all on the HGX baseboard).

Limitations & Controversies

  • PCIe interconnect ceiling : NVLink bridging is capped at 2/4 GPUs (600GB/s); interconnect density for large-scale training is far below the HGX SXM baseboard (per this database's compilation).
  • FP64 is not the focus : 30 TFLOPS FP64 — higher than the A100 (19.5 TFLOPS FP64) for double-precision HPC, but not Hopper's headline (per public reporting).
  • Training vs inference positioning : PCIe form factor + bridged interconnect — for large-scale training look to the HGX SXM series; the H100 NVL's sweet spot is inference and compliance.
  • Planning for configurable power : 350-400W configurable — the power tier places high demands on facility power and cooling flexibility; spell out the tier in the purchase contract.
  • Cross-border trade policy variables : The H100 NVL's export-control status toward China mirrors the H100 — consult professional counsel for cross-border procurement compliance; this database does not constitute legal advice.

Market Notes

H100 NVL spot supply runs in parallel: brand-new OEM units and pulls from decommissioned systems — AIXX Pedia honesty principle: no market band; prices are subject to the seller's quote 。

Spot search: AIXX Exchange Hall › (/hall.html?model=H100%20NVL) (Zero-commission Matching, hence neutral data).

Price milestone timeline

FAQ

The dividing line is deployment form factor: PCIe direct install (standard x86 tower/servers) → NVL; HGX baseboard systems (8-GPU NVLink all-to-all) suit large-scale training clusters. 94GB vs 80GB is a memory upgrade.

A direct memory upgrade: 141GB vs 94GB (+50%), 4.8TB/s vs 3.9TB/s bandwidth, FP8 in the same tier — the H200 NVL offers better cost per GB of memory for inference.

PCIe interconnect limitation (600GB/s bridging vs HGX 900GB/s all-to-all) — for large-scale training look at the HGX SXM series; the H100 NVL's sweet spot is inference and compliance.

Four steps: identity verification (nvidia-smi 94GB/ECC) → 400W-tier Full Load Burn-in Test (temperature/zero ECC errors) → FP8 compute benchmark (≥80% Pass, estimated figures) → MIG 7-instance partitioning test.

The H100 NVL's export-control status toward China mirrors the H100 — under licensing control since 2022-10. No new-card sales through legitimate mainland channels; circulation falls under stock and grey-market. Assess compliance risk up front; this database does not constitute legal advice.

Related Entries

Model comparison and selection

References

Video Overview

Vendor NVIDIA
Architecture Hopper
Memory 94GB HBM3
Bandwidth 3.9TB/s
FP8 / INT8 3,341 TFLOPS / TOPS
FP16 1,671 TFLOPS
FP64 / FP64 Tensor 30 / 60 TFLOPS
Interconnect NVLink 600GB/s
MIG Up to 7 instances @ 12GB
Encode/decode 7 NVDEC
Power 350-400W (configurable)
Form Factor PCIe dual-slot Air-cooled
Market No snapshot · Search spot listings in the hall › (/hall.html?model=H100%20NVL) (prices subject to the seller's quote)

Originally published on AIXX Pedia, the AI compute hardware encyclopedia maintained by the AIXX exchange team. Specs, pricing context and verified-inventory insights are updated there first.

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