One GPU, many workloads.
NUSAPOD manages your data-center GPU fleet: slice each GPU into right-sized VRAM partitions, provision pods on demand — empty or with an AI model — and let AI agents self-drive capacity. Maximum utilization, zero oversubscription.
VRAM slicingauto-provisioningself-driving agents
1 GPU
Split into many VRAM slices
Zero
Oversubscription, ever
Auto
Provisioning & self-driving agents
Full
Allocation & audit visibility
Everything to run a GPU fleet
From a bare GPU to a running pod
Slice VRAM into right-sized partitions, provision pods — empty or with an AI model from your model directory — and track every allocation, so no GPU sits half-idle.
How it works
From GPU to running pod in three steps
Model catalog
Curated, ready to deploy
Pick a model and it runs on vLLM behind an OpenAI-compatible endpoint in minutes.
deepseek-r1-671bdeepseek-v3-671bllama-3.1-405b-instructllama-4-maverick-400bqwen3-235b-a22bmixtral-8x22b-instructdbrx-instruct-132bcommand-r-plus-104bqwen2.5-72b-instructllama-3.3-70b-instructqwen2.5-coder-32bgemma-2-27b-itmistral-7b-instructllama-3.1-8b-instructqwen2.5-7b-instructphi-4+ bring your own