Hybrid CPU-GPU Inference Scheduler for Consumer Hardware
C6/10June 1, 2026
WhatAn inference engine that intelligently splits LLM workloads between CPU and integrated/discrete GPU on the same machine, routing matrix multiplication to the GPU and speculative decoding to CPU cores in real-time.
SignalMultiple commenters noted that consumer chips like AMD Strix Halo have both strong CPU cores and capable iGPUs, but no existing inference engine can efficiently use both simultaneously — everyone wants this but nobody has built it properly.
Why NowAMD's Strix Halo and Apple Silicon have created a new class of chips with powerful CPU+GPU on unified memory, and speculative decoding techniques have matured enough to make split-scheduling architecturally feasible.
MarketAI developers and power users on high-end laptops and workstations; adjacent to the $5B+ edge AI inference market; llama.cpp and vLLM don't do intelligent hybrid scheduling.
MoatRequires deep co-optimization across CPU architectures, GPU drivers, and memory hierarchies — a complex systems engineering moat that compounds with each hardware generation supported.
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