On-premise supercomputer for AI training — hardware you can actually own
A private LLM hardware stack is a rack plan, a compiler, and a jurisdiction — not a slide of 10,000 H100s you do not own.
Direct answer
You can buy Tenstorrent developer hardware on the public market. AGICY's campus fleet is pre-construction. Reserve via SRA or review planned GPU leasing — those are not COD hours.
Hardware stack for a private LLM
CISOs searching 'on-premise supercomputer for AI training' want weights, data, and interconnect inside a boundary they control. That is air-gap adjacent even when the hall is not literally unplugged.
AGICY's planned stack is Tenstorrent Galaxy / RISC-V for inference-heavy offtake, with compiler-first serving — not a promise that you can buy a secret NVIDIA allocation through us. Desktop TT boards exist; the Vasilikos fleet is planned.
Own the weights, or keep renting the API
Open-source vs closed-source AI security is the same decision: if you cannot export the weights and the traces, you do not own the model. Fine-tune on proprietary data only where the training run cannot be used as a vendor's future corpus.
Leasing planned Cyprus accelerators is the commercial path. Do not treat Phase 1 MW as live supercomputer time.
What to do next
GPU leasing (planned) · hardware · tenstorrent · Reserve SRA
Related markets and guides
- GPU data centers by EU country
- GPU data centers Cyprus
- GPU data centers Greece
- GPU Cloud for Enterprise EU
- AI Factory Setup Europe
- Open-Source LLM for Enterprise
FAQ
- Can I buy an on-premise supercomputer for AI training from AGICY today?
You can buy Tenstorrent developer hardware on the public market. AGICY's campus fleet is pre-construction. Reserve via SRA or review planned GPU leasing — those are not COD hours.
- What is a hardware stack for a private LLM?
Accelerators, CPU, network, storage, and a serving stack that never needs a US API. AGICY's planned path is RISC-V Galaxy plus Copperway for any overflow that must stay PII-masked.