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NPU / DSP 1-bit support — closure evidence

Verdict (decision-ready)

Vendor NPUs are INT8/INT4/FP16-first. Native 1-bit / 1.58-bit XNOR is not a drop-in path. Custom kernels required (rare). Product decision tree: INT8 on NPU; 1-bit on CPU (LCE / this repo) or FPGA (FINN); ternary LLM via bitnet.cpp or custom Hexagon.

Vendor Documented precisions Native 1-bit BNN? Source
Qualcomm HTP INT4, INT8, INT16, FP16 No in QNN stock Qualcomm AI hardware docs — HTP needs quantization to those types
Qualcomm BitNet Ternary needs custom Hexagon kernels Not stock ENERZAi: QNN has no ternary matmul; custom 1.58 kernels on QCS6490
Arm Ethos-U INT8 (and 16×8 act/wt modes) No Arm blog: Ethos-U is 8-bit integer; TFLite INT8 + Vela
Apple ANE / CoreML Weight 4/8-bit compress; runtime often float compute No 1-bit XNOR coremltools linear_quantize_weights n=4/8
This repo / LCE Packed binary on CPU Yes Local + Larq CE

Decision tree entry

Deploying on phone NPU?
├─ Stock SDK path → INT8 (or INT4 weights) via QNN / CoreML / Ethos+Vela
├─ Need BitNet ternary on Hexagon → budget custom kernels (non-trivial)
└─ Need classic W+A binary CNN → prefer CPU LCE or FPGA FINN, not stock NPU

Gap status

G_NPU / dim #15: CLOSED-BY-PROXY with primary vendor documentation (above). No further uncertainty for product thesis.