Stop Wasting
GPU Memory
VRAM dynamically swaps AI models in and out of VRAM — transparently, automatically, without changing a single line of your inference code.
$ docker run -e LICENSE_KEY=GSW1.xxx \
vramai/ghostswap:latest
✓ License valid: GROWTH | Acme Corp | 364d
✓ 1 GPU detected — RTX A40 48 GB
✓ VRAM gateway ready on :8080
✓ X-Ray dashboard at :8080/xray
# Swap model on first request
→ mistral-7b loading 14.2 GB ···
→ mistral-7b hot 0.8s
→ llama-3-8b evicted to NVMe
█
Everything you need to run more models
VRAM is a complete GPU memory virtualization stack — gateway, diagnostics, and Kubernetes deployment in one package.
Dynamic Model Swapping
VRAM transparently swaps AI models in and out of VRAM on demand — LRU eviction, NVMe spill, and prefetching built in.
X-Ray GPU Diagnostics
Real-time GPU waste scanner. See exactly which models are idle, how much VRAM is wasted, and what it costs per hour.
Multi-Model on One GPU
Serve dozens of models simultaneously on a single GPU. No dedicated VRAM per model — just a VRAM budget you set.
Zero-Change Integration
Drop-in OpenAI-compatible API. Point your existing inference code at VRAM — no SDK changes, no rewrites.
License-Controlled Access
Offline license validation with GPU and model limits baked in. No license server. No internet required at runtime.
Kubernetes Native
Production Helm chart included. GPU node affinity, PVC model storage, HPA, Prometheus ServiceMonitor — all pre-wired.
Model Compression
Shrink LLM weights 20–27× using Tensor-Train decomposition. Near-original accuracy after fine-tuning. Run bigger models on smaller, cheaper GPUs.
Up and running in minutes
Deploy VRAM on any NVIDIA GPU server or Kubernetes cluster.
Deploy VRAM
Pull the Docker image. Set your LICENSE_KEY. Configure your VRAM budget. Start in under 5 minutes.
Register Your Models
Add models via config or API. VRAM manages VRAM automatically — no manual loading or eviction.
Monitor with X-Ray
Open the X-Ray dashboard to see real-time GPU utilization, waste, and cost per model — then optimize.
See exactly where your
GPU money is going
X-Ray scans your fleet in real-time, identifies idle models, calculates the hourly dollar cost of each wasteful pattern, and tells you exactly what to fix.
- ✓ Real-time GPU utilization per model
- ✓ Idle VRAM cost in $/hr
- ✓ Waste patterns: memory leak, oversized batch, idle model
- ✓ Supports 30+ GPU types including cloud and on-prem
Ready to eliminate GPU waste?
Talk to our team about how VRAM fits your infrastructure.