LocalAI GPU Runtime.
Supercharged by Ada Lovelace & Blackwell.
A production-grade C++20 and CUDA runtime delivering sub-millisecond local generative AI inference, zero-fragmentation Paged KV-Cache, and sub-5µs CUDA Graph replay.
Architected by Pavan Kumar Sadashiv to bring sovereign, low-latency, and zero-egress generative AI directly to client-side workstations.
Paged KV-Cache Virtual Memory Architecture
Eliminating up to 70% VRAM waste by managing virtual-to-physical discrete 16-token memory blocks with radix prefix caching.
Zero-Fragmentation Virtual Tables
Dynamic virtual block table mapping allows sequences to occupy non-contiguous blocks in VRAM, achieving 0.00% memory fragmentation.
Immutable Prefix Caching
Hash-based prefix caching identifies shared system prompts and conversation history, sharing physical memory blocks with zero redundant compute.
Ultra-Fast 0.17µs Allocations
Pre-allocated VRAM pools and atomic bitmask allocation routines achieve sequence allocation speeds of 0.17 microseconds per request.
CUDA Graph Replay & Speculative Policy Loop
Sub-5µs CPU Driver Launch Latency
By pre-capturing entire layer GEMMs, attention kernels, and activation functions into static execution graphs, kernel launch overhead is bypassed, ensuring maximum Tensor Core utilization.
Up to 2.2x Acceleration (0.65 ms/tok)
A lightweight 1B draft model drafts 4 candidate tokens in parallel, evaluated simultaneously by the 8B target model in a single step with an 88.4% speculative acceptance rate.
Experience NVIDIA RTX-LocalAI in Real Time
Access the live interactive workbench, test token generation with custom prompts, view the physical 256-block memory map, and listen to the ElevenLabs voice briefing.