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NVIDIA and Foxconn announced their AI-factory collaboration on October 17, 2023. The idea is to build GPU computing infrastructure for processing data into AI models and tokens, then connect that compute to industrial uses such as manufacturing, robotics, electric vehicles, and generative AI. Later announcements outlined a planned Blackwell computing center in Kaohsiung, factory digital-twin work, and a Taiwan AI-factory cloud project. Those announcements describe plans and company claims, not independently verified operational results.
What is an AI factory?
In its 2023 announcement, NVIDIA defined an AI factory as “an NVIDIA GPU computing infrastructure specially built for processing, refining and transforming vast amounts of data into valuable AI models and tokens.” That is NVIDIA’s description of the concept, not a neutral industry standard. The analogy is that a conventional factory turns raw materials into products, while this kind of computing facility is designed to turn data and computing capacity into AI outputs.
NVIDIA’s framing emphasizes the full AI workload: training models, running inference, and supporting the software and workflows around those tasks. The 2023 Foxconn announcement named NVIDIA’s GH200 Grace Hopper platform and NVIDIA AI Enterprise, and described simulation of factory workflows before physical deployment as an intended use.
What did NVIDIA and Foxconn announce?
The October 2023 partnership
The companies presented the collaboration as both infrastructure and applied industrial AI. Foxconn planned to integrate NVIDIA technology into data centers and develop applications for manufacturing, inspection, robotics, AI-powered electric vehicles, smart cities, and generative AI services.
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The announced platform plans included Foxconn Smart EV work using NVIDIA DRIVE Hyperion 9 and DRIVE Thor, robotics for smart manufacturing using Isaac, and smart-city applications using Metropolis. These are named plans from the announcement, not proof that every platform or service has since been deployed.
The June 2024 Kaohsiung plan
Foxconn said it planned to build an advanced computing center in Kaohsiung, Taiwan, with NVIDIA Blackwell at its core. The announcement placed the project within a broader collaboration spanning AI, electric vehicles, smart factories, robotics, and smart cities. It described a plan to build the center; it did not establish that the facility was completed or operational. Foxconn’s June 4, 2024 announcement.
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Factory digital twins in November 2024
Foxconn described work with NVIDIA on digital twins for manufacturing processes and supply-chain management, including activity connected with its Mexico factory. The named technologies were Omniverse, Isaac, Modulus, and OpenUSD. A digital twin is a virtual representation used to model or simulate a physical system; in this context, the stated purpose was to support factory and supply-chain processes. The announcement did not report quantified productivity gains. Foxconn’s November 19, 2024 announcement.
The May 2025 Taiwan AI-factory cloud project
On May 18, 2025, NVIDIA said Foxconn and Taiwan’s government were working on an AI-factory supercomputer. Foxconn subsidiary Big Innovation Company was to provide the infrastructure as an NVIDIA Cloud Partner. NVIDIA announced 10,000 Blackwell GPUs for the planned system, including Blackwell Ultra systems such as GB300 NVL72, alongside NVIDIA Quantum InfiniBand and Spectrum-X Ethernet. NVIDIA named TSMC as a user of the cloud infrastructure for research and development. These are details of the announced project, not independent confirmation of its current operating status or performance. NVIDIA’s May 18, 2025 announcement.
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How is an AI factory different from a regular data center?
An AI factory is best understood as a purpose-and-workload description for computing infrastructure, not necessarily a wholly separate kind of building. NVIDIA uses the term for GPU systems designed around AI work: preparing and processing data, training models, serving inference, and producing outputs such as tokens. The Foxconn announcements also tie that compute to industrial applications and simulation.
The cited company announcements do not provide a neutral technical comparison with conventional data centers, such as a controlled comparison of hardware, power use, cost, or performance. So the useful distinction is what the infrastructure is intended to do, rather than a claim that every AI factory differs physically from every other data center.
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What the Foxconn projects could mean in practice
- AI model work: GPU compute can be used for training and inference, although the announcements do not disclose achieved throughput or benchmark results for the named projects.
- Factory planning: Digital twins and simulation can let teams model manufacturing processes or supply chains in a virtual environment before making changes in a physical operation. Foxconn’s announcement identifies tools and intended applications, not measured savings.
- Industrial services: The original collaboration covered proposed use cases in robotics, vehicle platforms, inspection, smart cities, and generative AI services. The announcement establishes the scope of the plans, not their realized outcomes.
- Cloud access: The Taiwan project was presented as a cloud route to AI-factory compute, with Big Innovation Company acting as an NVIDIA Cloud Partner. That differs from assuming each user owns and operates the underlying GPU infrastructure.
How to assess an AI-factory proposal
The announcements establish several dimensions that matter when evaluating a project, but they do not provide a vendor-neutral scorecard or like-for-like pricing and performance data.
| Decision area | What to ask | What the Foxconn announcements establish |
|---|---|---|
| Workload | Is the compute for model training, inference, or both? | The 2023 announcement described training and inference as intended capabilities; project-level workload volumes and results were not stated in the cited announcements. |
| Industrial task | Will the system support simulation, a digital twin, or a live production workflow? | The announcements described virtual factory workflows and digital twins for manufacturing and supply-chain processes; quantified impact was not stated. |
| Delivery model | Will the organization operate its own infrastructure or use cloud access? | The 2025 Taiwan project was announced as cloud infrastructure provided by Big Innovation Company; the 2024 Kaohsiung project was described as a planned computing center. |
| Economics and service levels | What are the cost per useful output, utilization, uptime, and energy demands? | NVIDIA’s current AI-factories page discusses tokens per second, tokens per watt, cost per token, utilization, and uptime as evaluation metrics. Foxconn project results for these measures were not stated. NVIDIA’s AI-factories page. |
What is—and is not—established
The cited releases are company announcements. They establish what NVIDIA and Foxconn said they planned or were building toward, but do not independently verify present operational status, measured performance, cost savings, productivity gains, or energy efficiency for the projects. NVIDIA’s AI-factory metrics are useful company-proposed ways to frame economics, not reported results for Foxconn’s facilities. No neutral, independently measured figure in these announcements establishes market-wide AI-factory adoption or the collaboration’s achieved output.
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