COMPUTE · LUPINE

On-demand GPUs.
Zero idle cost.

Lupine is Numerata's compute layer: GPUs that scale to zero when idle, aggregate across machines into one pool, and need no code changes to use. Private cloud by default, or fully air-gapped.

Visit site →

HOW IT WORKS

A drop-in CUDA shim, not a new API to learn.

DROP-IN CUDA SHIM

Transparent driver shim that works with PyTorch, TensorFlow, and JAX out of the box. Supports cuBLAS, cuDNN, and NVML, so existing code runs unmodified.

MULTI-GPU AGGREGATION

Our coordinator exposes a unified device list across machines, turning scattered GPUs, on-prem or in the cloud, into one pool you can schedule against.

LOW OVERHEAD

CUDA calls are proxied transparently over a plain HTTP/2 protocol, with minimal serialization overhead. Bring your own TLS, auth, or load balancing.

QUICKSTART

Two containers. No SDK, no provisioning step.

SERVER: run where the GPU lives

docker run --rm --gpus all -p 14833:14833 \
  ghcr.io/lupinemachines/lupine-server:cuda-13.1.0-ubuntu24.04

CLIENT: connect from any machine (mac, linux, arm, x86)

docker run --rm -it \
  -e LUPINE_SERVER=<server>:14833 \
  ghcr.io/lupinemachines/lupine-client:cuda-13.1.0-ubuntu24.04 \
  nvidia-smi

USE CASES

Spin up GPUs on demand,
scale to zero when idle.

Run inference at scale
without managing servers.

Fine-tune models
without reserved capacity.

STATUS

Early access today. Lupine Cloud is next: serverless GPUs with sub-second cold starts and consumption-based pricing.

Join early access →