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Research context · not a recommendation

NVIDIA (NVDA)

Descriptive positioning only. The positioning label says whether a company's business is exposed to a layer, never whether to buy it. Layers with no exposure are not recommendations to add any.

Stack position

Where NVDA sits in the AI stack

  1. L3 · Semiconductor Equipment

    Lithography, etch, deposition, inspection, and advanced packaging tools.

  2. L3b · Foundry

    Contract wafer fabrication and advanced packaging that turn accelerator designs into silicon.

  3. L4 · Compute

    GPUs, AI accelerators, and general-purpose compute silicon for training and inference.

  4. L4 · HBM / Memory

    HBM/DRAM bandwidth beside accelerators, plus enterprise NAND/HDD capacity. US-listed tickers or ADRs only.

Icons mark layer roles — not company logos. Position only; not a price chart.

L4 · Compute

XingAI taxonomy. Filers did not assign this layer.

Map role vs this layer: Primary business sits here. Describes where the business sits, not a trade.

NVIDIA

Products on file: Data-center GPUs, HGX, NVL72

What does NVIDIA do in this layer?

Supplies data-center GPUs and rack-scale systems for AI training and inference.

Why does this layer matter for AI demand?

The visible centre of the chain, and the layer most people stop at. It is also the layer that cannot run alone: an accelerator needs memory bandwidth, packaging, interconnect, optics, storage, power and cooling around it. Any one of those lagging and the silicon idles.

What could change the picture here?

Design leadership concentrates here, but the near-term ceiling is usually set elsewhere — packaging, HBM supply, or power — rather than by accelerator design.

Same-layer companies (alphabetical, not ranked)

AMD ARM AVGO CBRS INTC

  • AMD — Supplies Instinct data-center GPUs used for AI training and inference.
  • ARM — Licenses CPU architecture and Neoverse designs that partners build into data-center and cloud AI chips.
  • AVGO — Designs customized system-on-chip ASICs for customers' own systems, including AI accelerators.
  • CBRS — Builds wafer-scale AI systems, currently marketed for fast inference.
  • INTC — Supplies Xeon data-center CPUs used for AI, HPC and general-purpose workloads, and Gaudi AI accelerators.

Open the Compute layer

Weekly digest: AI-map layer changes and new public 13F filings, each with its source. No score, no grade, no trade signal. Unsubscribe anytime.

Cache snapshot 2026-10-20. Filing dates below are the source dates, not this snapshot.

Public 13F rows

Rows below are public SEC Form 13F-HR filings, reported by the filing entity for the period shown and filed later — they are never current holdings. Form 13F covers long US equity positions only: it excludes short positions, cash, non-US holdings and most derivatives, and a reported position may have been sold since. Assigning a ticker to a layer is XingAI's classification, not the filer's. Nothing here is a recommendation, and an institution reporting a position is not a reason to take one.

What this page does not answer

Valuation, a target price, and when to buy or sell. Those are not in the cache, and this page will not guess them.

Research questions

  • Which layer is this company's primary business in, on XingAI's taxonomy?
  • Which public Form 13F-HR rows cite this ticker, and when were they filed?
  • Who else in the same layer is listed, alphabetically — not ranked?

Weekly digest: AI-map layer changes and new public 13F filings, each with its source. No score, no grade, no trade signal. Unsubscribe anytime.

    NVIDIA (NVDA) · AI supply chain · Compute · XingAI Invest AI