Add measured Galaxy S26 NPU/GPU encoder rows

README.md

@@ -209,6 +209,22 @@ model reproduces the f32 token sequence exactly on the dense test window on
 both Apple devices, and its transcripts are identical between the M4 Max
 and the Pi 5 on all 12 test clips.
 
+### Snapdragon NPU / GPU — Galaxy S26
+
+Measured on a physical Samsung Galaxy S26 (SM-S942Q, Snapdragon 8 Elite Gen 5 / SM8850, Hexagon v81, Android 16) with LiteRT `CompiledModel` 2.2.0 — 5 warm-up runs then 50 timed runs, one accelerator per process, every row at device thermal status `NONE`, delegate placement confirmed from logcat per row. The figures are the **`encode` signature only** (the model's first signature, which the API's default `run()` executes — the encoder over the raw 80,000-sample / 5 s waveform input); not comparable to the end-to-end window totals in the CPU table above. NPU in HTP BURST mode, on-device (JIT) compilation.
+
+| File | Compute unit | Encode (median / min) | Load |
+|---|---|---|---|
+| `moonshine_tiny_5s_f32.tflite` | **GPU (Adreno)** | **5.4 ms** / 5.4 ms | 1.7 s |
+| `moonshine_tiny_5s_i8.tflite` | NPU (Hexagon, JIT) — first launch | 1294 ms / 1281 ms | 13.1 s |
+| `moonshine_tiny_5s_i8.tflite` | NPU (Hexagon, JIT) — cached | 1264 ms / 1247 ms | 0.37 s |
+
+What the table says:
+
+- **On this device the GPU running the f32 file is the only fast accelerated path**: 5.4 ms for the 5 s window's encoder, encoder-only RTF 0.001.
+- **The Hexagon runs the i8 encoder in ~1.26 s** — slower than the Pi 5's CPU in the table above. The two accelerators also refuse each other's file: f32 compiles for the NPU but fails at output-buffer creation, and i8 fails to compile on the GPU. So there is no NPU recommendation to make from this run.
+- `moonshine_tiny_5s_f32_Qualcomm_SM8850.tflite` (the embedded precompiled context) failed to invoke on both accelerators in this harness and is not quoted.
+
 ### Accuracy note
 
 In a 12-clip spot check (LibriSpeech dev-clean samples plus two