card: Neural Engine bundle section

README.md

@@ -81,6 +81,21 @@ conversation history; `streamResponse(to:)` yields tokens as they decode.
 - Measure in Release — Debug is ~3× slower on per-token host work
 <!-- gen-cards:use-it end -->
 
+## Neural Engine bundle (iOS static export, AOT h18p) — 2026-09-15
+
+`ios-ane-h18p/` is Apple's stock `coreai.llm.export --platform iOS` static export of this checkpoint
+(k-means **4-bit palettized, group 32** (Apple's iOS default preset); embeddings int8; static graphs `prompt_opt`/`extend` ×
+contexts {256, 512, 1024, 2048, 4096} × query {8, 16, 64}), AOT-compiled with
+`xcrun coreai-build compile --platform iOS --preferred-compute neural-engine --architecture h18p`
+(31/31 ANE regions, 1.4 GB). It loads through Apple's `EngineFactory` → `StaticShapeEngine` unchanged
+(iPhone 17-class devices). `ios-static/` is the same export before AOT — the portable IR; compile it
+for another chip yourself. 
+
+Gated on an iPhone 17 Pro (iOS 27.0) against the fp32 HF oracle: teacher-forced single-step sweep 24/24 + 8/8 + 16/16 and free-run greedy token-exact including the stop — transcript in the zoo,
+`models/minicpm5-2b/gate-minicpm5-2b-ane-device.json`. Speed on the same phone (Apple llm-benchmark
+method, 512-token prompt, 1024 generated, 5 trials, two back-to-back runs): decode **48.0 / 38.2 tok/s**, prefill 1858 / 1494 tok/s; footprint 2.0 GB. The Neural Engine is the power-efficient lane; these are
+not a GPU comparison (different protocol from the `int8/` row above).
+
 ## Measured
 
 | | decode | prefill | numerics | size |