Add measured Snapdragon NPU / GPU section (Galaxy S26)

Numbers from the 2026-08-23 Galaxy S26 sweep. Primary log:
litertlm-convert/portal_work/bench_all.txt + bench_redo.txt, summarised in
portal_work/NOTES.md (2026-08-23, the 50-model NPU/GPU comparison).
Every row carries device, SoC, runtime, N and thermal state. Measurements
are joined to this repo by exact .tflite file name.

README.md

@@ -138,6 +138,18 @@ On this delegate the CPU is the faster choice for (9.8 ms on CPU against 53.0 ms
 
 Note that the GPU does not take the whole graph here (71 / 455); the remainder runs on the CPU and the split costs a per-partition round trip.
 
+## Snapdragon NPU (Hexagon)
+
+The GPU delegate declines this graph on the S26: `LiteRtException: Failed to compile model`. The NPU runs it at 2.15 ms.
+
+| backend | inference (median / min) | load |
+|---|---:|---:|
+| NPU (Hexagon v81) | 2.15 ms / 2.09 ms | 112 ms |
+
+Measured on a **Samsung Galaxy S26** (Snapdragon 8 Elite Gen 5 / SM8850, Hexagon v81, Android 16), LiteRT `CompiledModel` 2.2.0, one accelerator per process, 5 warm-up runs then N=50 timed runs, median reported. The run held thermal status `NONE` throughout. Headroom 0.68, where 1.0 is the throttling threshold.
+
+The NPU rows here ran artifacts compiled ahead of time for SM8850 with QAIRT 2.47.0. LiteRT can also compile for the NPU on the device at first load, which is what lets you ship the published file unchanged — that path and the ten runtime libraries it needs are in the [NPU recipe](https://github.com/john-rocky/hf-to-litertlm/blob/main/docs/android-npu.md), and we did not measure it here. GPU wiring is in the [GPU recipe](https://github.com/john-rocky/hf-to-litertlm/blob/main/docs/android-gpu.md).
+
 ## License
 
 Apache-2.0 (MoViNet / Atze00/MoViNet-pytorch). Kinetics-600 label taxonomy from the