Add measured Raspberry Pi 5 (CPU) section

Numbers from the 2026-08-31 Raspberry Pi 5 sweep: LiteRT benchmark_model
(litert-cli-nightly 0.2.0.dev20260805), CPU/XNNPACK, 4 threads, 10 warm-up +
50 timed runs x 3 invocations per file, cooldown between invocations, thermal
throttle state verified 0x0 on every run. Median + spread, never single-shot.
Measurements are joined to this repo by exact .tflite file name.

README.md

@@ -127,6 +127,14 @@ Measured on a **Samsung Galaxy S26** (Snapdragon 8 Elite Gen 5 / SM8850, Hexagon
 
 The NPU rows here ran artifacts compiled ahead of time for SM8850 with QAIRT 2.47.0; the GPU rows ran the published files as they are. 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).
 
+## Raspberry Pi 5 (CPU)
+
+Measured on a Raspberry Pi 5 Model B Rev 1.1 (8 GB, Raspberry Pi OS 64-bit) with the LiteRT [`benchmark_model`](https://ai.google.dev/edge/litert/models/measurement) tool from litert-cli-nightly 0.2.0.dev20260805: CPU inference (XNNPACK, 4 threads), 3 invocations per file of 10 warm-up plus 50 timed runs (the tool caps a phase at 150 s, so very slow graphs run fewer — the Runs column is the actual timed total). The latency is the median across invocations; the spread is the min–max over all timed runs. No thermal throttling occurred during these runs (`vcgencmd get_throttled` stayed `0x0`).
+
+| File | Inference (median) | Spread (min–max) | Runs | Peak memory |
+|---|---:|---:|---:|---:|
+| `vrwkv_s_fp16.tflite` | 1,082.6 ms | 1,075.0–1,128.4 ms | 150 | 277 MB |
+
 ## License
 
 Apache-2.0 (Vision-RWKV / OpenGVLab). Converted with litert-torch.