WhatAn infrastructure layer that manages SSD-backed KV cache persistence for local LLM sessions, eliminating expensive re-prefill when context windows fall out of memory.
SignalUsers running large context windows locally describe painful workflow interruptions when sessions drop from memory and need to re-process 50K+ tokens, and those who have found caching solutions call it a game-changer for agent workflows.
Why NowAgent-based workflows with massive context windows are becoming the dominant use pattern, and Apple Silicon's unified memory + fast SSD architecture makes persistent KV caching technically viable for the first time.
MarketPower users and developers running local LLMs for agent workflows; omlx.ai is early mover but the space is nascent. Could be infrastructure sold to app developers or direct to consumers. TAM $200M+ as local inference grows.
MoatDeep integration with specific model architectures and hardware memory hierarchies creates technical complexity that's hard to replicate; early performance benchmarks and reliability data compound over time.
Ollama is now powered by MLX on Apple Silicon in previewView discussion ↗ · Article ↗ · 623 pts · March 31, 2026
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