The headline describes a June 2019 snapshot—not a current market ranking. EE Times reported that NVIDIA appeared in 97.4% of dedicated-accelerator cloud instance types, while Intel processors appeared in 92.8% of compute instance types. Those percentages describe different categories, so they do not show NVIDIA beating Intel in a direct, like-for-like share comparison.
What did the 2019 figures measure?
In an article published June 14, 2019, Paul Teich, then identified as principal analyst for Liftr Cloud Insights, reported figures for instance types offered by the top four public-cloud services. EE Times attributed the figures to Liftr; the article does not provide enough detail to reconstruct the provider list, sampling, or counting method. EE Times’ June 2019 report
| Measure reported | Share | What it represents |
|---|---|---|
| NVIDIA GPUs | 97.4% | Dedicated-accelerator instance types |
| Intel processors | 92.8% | Compute instance types |
| AMD processors | 4.2% | Overall processor instance types |
The first two percentages have different denominators: NVIDIA’s figure is about accelerator instance types, while Intel’s is about compute instance types. They should not be read as competing shares of one common cloud-computing market.
How did other accelerator options compare?
Within the dedicated-accelerator instance types in that report, AMD GPUs accounted for 1.0%, matching Xilinx Virtex UltraScale+ FPGAs at 1.0%; Intel Arria 10 FPGAs accounted for 0.6%. These are historical figures from the same 2019 snapshot, not present-day availability or market shares.
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Teich argued at the time that NVIDIA’s deeper, more mature deep-learning software capabilities helped explain its competitive position. That is his 2019 analysis, not a timeless finding established by the reported percentages alone.
What did the report say about CPUs and Arm?
The article noted that cloud providers sometimes left the processor unspecified in an instance type. Liftr reduced the unspecified share—processors known to be x86-64—to 2.8%. It also reported AWS Graviton as the only Arm processor then deployed across the top four cloud services, at 0.2% of their overall compute instance types. These figures describe the 2019 snapshot only.
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Do later estimates update the 2019 cloud comparison?
No. The OECD’s 2025 working paper develops a method for tracking public-cloud AI compute by recording accelerator availability by region. Its pilot used data collected in October 2023, covered six providers and five GPU types, and was described as illustrative rather than final. The method records whether accelerators are available in a region; it does not count chips or measure compute capacity within that region. The pilot also excluded custom accelerators such as Google TPUs, so it is not a direct update to Liftr’s 2019 instance-type figures. OECD, Mapping the Global Landscape of Cloud Computing Capacity for Artificial Intelligence (2025)
The OECD paper also cites an estimate that NVIDIA comprises 88% of the total accelerator market, with AMD at 12% and Intel at 1%. The paper attributes that estimate to Batt (2024); it is not an OECD survey of cloud instance types. Its scope should not be conflated with the Liftr cloud snapshot.
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The paper’s proposed coverage of nine providers represents over 70% of global public-cloud spending, but the OECD cautions that this is public-cloud computing overall, not public AI compute specifically. Provider spending shares therefore cannot be substituted for accelerator or chip shares.
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What can a reader conclude?
- The headline refers to a report published on June 14, 2019, rather than a current ranking.
- NVIDIA’s reported 97.4% concerned dedicated-accelerator instance types; Intel’s 92.8% concerned compute instance types. They are not directly comparable shares.
- Later OECD work offers a different, region-availability measure and an incomplete pilot, not a like-for-like update of the 2019 instance-type data.
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