Enterprise-Grade SSD-Based VRAM Cache Swapping for LLM Training & Inference
Revolutionary SDK that enables running 70B+ parameter models on consumer hardware through intelligent memory tiering across GPU VRAM, DRAM, and SLC NVMe SSDs.
Revolutionary Memory Tiering
Our patented 3-tier memory architecture extends GPU VRAM by 10-20x, enabling you to run 70B+ parameter models on consumer hardware.
L1 • GPU VRAM
Fastest memory tier with 16-24GB capacity. Stores active model layers and KV cache for immediate access.
Enterprise-Grade Capabilities
Built for production workloads with cutting-edge optimizations
10-20x Memory Extension
Run 70B+ parameter models on consumer GPUs. Extend your VRAM capacity dramatically without expensive hardware upgrades.
Sub-second TTFT
Lightning-fast time to first token. Start generating responses in under a second, even with massive models.
Intelligent Prefetching
ML-powered prediction engine anticipates your needs. Preload model layers before they're required for seamless performance.
Hardware-Agnostic
Works with any GPU, any SSD. No vendor lock-in. Deploy on your existing infrastructure without restrictions.
PyTorch/HF Integration
Drop-in replacement for your existing workflows. Zero code changes required - just install and run.
Enterprise Monitoring
Comprehensive observability with real-time metrics, alerts, and performance analytics built for production.
Auto Memory Management
Set it and forget it. Intelligent algorithms handle memory allocation, offloading, and optimization automatically.
Multi-GPU Support
Scale across multiple GPUs seamlessly. Automatic load balancing and efficient memory distribution across devices.
Quantization Optimization
Advanced quantization techniques reduce model size while maintaining accuracy. Get the best performance-to-quality ratio.
Custom Training Loops
Full flexibility for advanced use cases. Support for custom training loops, fine-tuning, and specialized workflows.
How It Works
Intelligent Memory Management
Our SDK automatically analyzes memory usage patterns and intelligently offloads inactive model layers and KV cache to the optimal tier.
Predictive Prefetching
Advanced algorithms predict which model components will be needed next, preloading them into faster memory tiers before they're required.
Seamless Integration
Drop-in replacement for existing PyTorch workflows. No code changes required - just install and run your models as usual.
Performance Optimization
Optimized For Every Workload
From research to production, scale your AI workloads with confidence
Large Model Training
Train 70B+ parameter models on consumer hardware
Production Inference
Deploy large models in production with optimal performance
AI Research
Enable researchers to experiment with large models
Enterprise AI
Deploy AI solutions at scale with enterprise reliability