Run 500B-parameter LLMs locally

Bring frontier-scale models on-prem: fast, private, and self-contained.

The Problem

Modern AI infrastructure has hard constraints:

  • Cloud reliance Ongoing cost, latency, and data exposure
  • GPU ecosystem lock-in Limited supply, high pricing
  • Consumer hardware ceilings Not designed for large-scale inference

The Solution

GPU optimised for Inference.

  • Run advanced LLMs locally
  • Keep data fully on-device
  • Eliminate external dependencies

Product Status

In development:

  • TiniGPU Compact inference hardware
  • TiniLLM CLI Local model runtime for developers
  • TiniQuant High-efficiency model compression