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docs: ship iOS 17 as the canonical build (verified speed/WER parity with iOS 18)

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  1. README.md +6 -7
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@@ -152,12 +152,11 @@ benchmark numbers.
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  ### iOS 17
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- The default `latin/` and `multilingual/` bundles target **iOS 18+** (they use an
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- iOS 18-only quantization op). A parallel **`ios17/`** tree
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- (`ios17/latin/<tier>ms/`, `ios17/multilingual/<tier>ms/`) mirrors them for
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- **iOS 17**, built from the same recipe re-targeted to iOS 17. WER is identical;
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- on iOS 18 hardware the iOS 17 build runs ~4% slower (it uses the older dequant
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- op), which is why both are shipped. Use `ios17/` only if you need iOS 17 support.
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  ## Notes
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@@ -172,7 +171,7 @@ op), which is why both are shipped. Use `ios17/` only if you need iOS 17 support
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  ## Benchmark methodology
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- Apple M5 Pro, macOS 26.5, coremltools 9.0, CoreML iOS18 target,
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  `.cpuAndNeuralEngine` routing. Single-stream, batch=1, per-file sum-aggregate
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  RTFx (matches the Open ASR Leaderboard convention). **All languages evaluated
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  on FLEURS test, full splits.** WER for Latin-script languages, CER for zh/ja,
 
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  ### iOS 17
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+ All `latin/` and `multilingual/` bundles target **iOS 17+ / macOS 14+**. The
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+ encoder uses an iOS 17-compatible quantization (INT8 cuff via `affine_dequantize`
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+ + 6-bit palettized middle); the 6-bit middle is unchanged from the prior iOS 18
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+ build. Speed and WER are identical to that iOS 18 build verified on LibriSpeech
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+ test-clean (M5 Pro, 2 s tier): **120 RTFx, 3.67% WER** for both targets.
 
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  ## Notes
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  ## Benchmark methodology
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+ Apple M5 Pro, macOS 26.5, coremltools 9.0, CoreML iOS 17 target,
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  `.cpuAndNeuralEngine` routing. Single-stream, batch=1, per-file sum-aggregate
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  RTFx (matches the Open ASR Leaderboard convention). **All languages evaluated
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  on FLEURS test, full splits.** WER for Latin-script languages, CER for zh/ja,