From the NVIDIA edition of November 1, 2026
MOEA's sixth Taipei-1 call sets the terms for free NVIDIA H100 and L40 compute: whole-system blocks, non-commercial use, no sensitive data, non-negotiable NVIDIA contracts
Taiwan Ministry of Economic Affairs, Department of Industrial Technology (A+ programme office); NVIDIA · Government-administered access to a vendor-run AI supercomputer · Taiwan
- Publisher
- MOEA Department of Industrial Technology, A+ Enterprise Innovation R&D programme
- Original publication
- 2026-06-02 (background; newly relevant as MOEA negotiates the next phase)
- Source retrieved
- 2026-11-02
- Event date
- 2026-06-02
What happened
The sixth call, which allocates the remaining time to February 26, 2027, offers Taiwanese companies, schools, research institutes and start-ups free Taipei-1 compute, which NVIDIA shares from July 2024 to February 2027. Capacity is 16 DGX H100 systems (8 GPUs each) and 8 OVX 2.0 systems (8 L40 GPUs each). A team must take all 16 DGX for six weeks (four of them computing, plus onboarding and offboarding) or all 8 OVX for twelve weeks; smaller users must apply jointly. Review weighs commercial potential and large-compute experience. Use must be non-commercial. Users must not process or enter proprietary or sensitive information. NVIDIA's NDA and user agreement are standard and cannot be changed. NVIDIA headquarters operates the system, and publicity naming Taipei-1 needs NVIDIA's approval.
Why it matters
This is a detailed public rulebook for sharing a vendor's AI supercomputer with universities and firms. States and university consortia designing shared compute can reuse its allocation model and should note its data and contract limits.
Evidence and measured results
Primary government call notice with eligibility, capacity, schedule and terms; it does not report usage or results.
Limitations and uncertainty
Published June 2, filed as background because the Nov 1 report says the current phase is ending and a next phase is under negotiation. The notice covers this call only.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-02; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Public research users lack access to large GPU systems.
- Stakeholders
- University research computing
- State economic development
- Vendor
- Discovery questions
- Can users bring sensitive data?
- Who controls publicity and results?
- Value hypothesis
- A clear allocation model widens access to scarce compute.
- Potential engagement
- Design review for a shared-compute programme.
- Unsupported claims
- Any usage or outcome figures
- Suitability for regulated data
Pre-sales engineering
Role takeaway
- Fit
- Relevant to shared training-scale compute.
- Architecture and integration
- Scheduled whole-system blocks on DGX H100 and OVX L40 clusters.
- Prerequisites
- Job-ready code
- Public or synthetic datasets
- Constraints
- No proprietary or sensitive data
- Six- or twelve-week blocks only
- Non-commercial use
- Security
- Sensitive data is barred; vendor runs the system.
- Proof of value
- Proposed: dry-run jobs before the window
- Proposed: checkpoint plan for maintenance windows
Delivery
Role takeaway
- Work
- Run the call, review and reporting process.
- Dependencies
- Vendor contracts
- Review panel
- Ownership
- Programme office.
- Skills and adoption
- Train applicants to form joint proposals.
- Governance checkpoints
- Eligibility and data review
- Post-use disclosure
- Acceptance criteria
- Proposed: every allocated block fully used
- Risks
- Unused blocks
- Data-rule breaches
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Whole-system time blocks favour large training runs and force small users to pool projects.
Governance
Who approves, reviews and stays accountable for outcomes?
Results disclosure follows government requirements, and generative AI use must be disclosed under Executive Yuan guidance.
Security and privacy
What data, permissions and controls need testing?
The ban on proprietary or sensitive data rules out regulated public-sector data.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Universities and start-ups get access to H100-class systems they could not buy.
Procurement
What should contracts, pricing and exit terms secure?
Vendor contracts are fixed; the public side cannot negotiate user terms per project.
Operating model
Which teams own the service once it runs?
The vendor sets maintenance windows with two weeks' notice and controls publicity.
Publication history
- 2026-11-01NVIDIA · Issue 575 resources
Stable resource ID: taiwan-moea-taipei1-sixth-call-terms-free-h100-compute-20260602