Card: iPhone 17 Pro results (Mieru proof of concept, 2026-10-13)

README.md

@@ -20,6 +20,16 @@ D1A is a small open decision model. One document and a set of typed questions go
 - PR change type: 87.3% against 87.5%, −0.2 [−3.1, +2.7] (no measurable difference);
 - photos, voice and video: all 14 demo requests answered, but **21 of 28** answers match E4B v0.6, where E2B v0.6 matches 25.
 
+**On the iPhone (2026-10-13, iPhone 17 Pro, in the Mieru app):** this model runs as an unmerged LoRA adapter on the app's
+own Gemma 4 E2B-it 4-bit, so it is one model in memory.
+- **Accuracy:** 0 of 42 answers differ from the Mac.
+- **Speed and memory:** 0.52 s per request; the adapter adds 25 MB.
+- **Base untouched:** with the adapter off, the hidden states are bit-identical to the base.
+
+The Core ML 4-bit build also matches the Mac on the phone (0 of 42; 0.66 s on its GPU). First use case: deciding whether a
+new camera description is worth speaking (redundant / vague → skip / re-capture / speak). It took the intended action on
+8 hand-written test cases, which is a smoke test, not a measurement.
+
 Everything else (hard, developer-tool and long-document decisions, held-out transfer, general decisions, Japanese) is **not measured yet** on this build. Do not assume E2B v0.6's numbers carry over.
 
 **Release note.** The bar registered for this run before training (jonpol01/d1a#227, Bar B, "good enough for apps") failed on two lines: severity −4.3 (it needed −3 or better) and media agreement 21/28 (it needed 25/28). It is published by the owner's decision of 2026-10-12 for the iOS proof of concept, as a separate repository and not as E2B's model.