Merge feature/20 into integration/spec16 (ticket #20: measured ladder thresholds)
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@@ -8,13 +8,12 @@ Rungs (quantized Turbo first, small floor last)::
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large-v3-turbo-q8_0 -> large-v3-turbo-q5_0 -> small.en / small
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Thresholds derive from the catalog on-disk sizes (874/574 MiB) plus the
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512 MiB desktop headroom from the locked baseline protocol
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(``scripts/measure_perf_baseline.py::recommend_thresholds``). Ticket #19
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recorded no measured per-rung footprints, so these are size-plus-headroom
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proxies: recalibrate them from hardware numbers when they land. The
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derivation is pinned by ``tests/test_model_ladder.py`` so a catalog size
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bump forces a threshold review.
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Thresholds derive from ticket #19's measured transcribe peaks (1132 MiB
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for q8_0, 846 MiB for q5_0) plus the 512 MiB desktop headroom from the
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locked baseline protocol
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(``scripts/measure_perf_baseline.py::recommend_thresholds``). The
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derivation is pinned by ``tests/test_model_ladder.py`` so a re-measure
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forces a threshold review.
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Backend order follows the same readiness rule: CUDA ranks before Vulkan
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only when a complete architecture-matching CUDA toolkit is installed
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@@ -40,14 +39,14 @@ LADDER_RUNGS: tuple[str, ...] = (DEFAULT_RUNG, LOW_MEMORY_RUNG)
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#: the baseline protocol adds to measured footprints.
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HEADROOM_MIB: float = 512.0
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#: Catalog on-disk sizes (MiB) the thresholds below are derived from.
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_Q8_0_SIZE_MIB: float = 874.0
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_Q5_0_SIZE_MIB: float = 574.0
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#: Ticket #19 measured transcribe peaks (MiB) the thresholds below derive from.
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_MEASURED_Q8_0_PEAK_MIB: float = 1132.0
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_MEASURED_Q5_0_PEAK_MIB: float = 846.0
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#: Free memory at or above this keeps the default q8_0 rung.
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PREFER_Q8_0_ABOVE_MIB: float = _Q8_0_SIZE_MIB + HEADROOM_MIB
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PREFER_Q8_0_ABOVE_MIB: float = _MEASURED_Q8_0_PEAK_MIB + HEADROOM_MIB
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#: Free memory at or above this keeps the q5_0 rung; below it is the floor.
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PREFER_Q5_0_ABOVE_MIB: float = _Q5_0_SIZE_MIB + HEADROOM_MIB
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PREFER_Q5_0_ABOVE_MIB: float = _MEASURED_Q5_0_PEAK_MIB + HEADROOM_MIB
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#: Minimum CUDA compute capability (major, minor) the bundled backend
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#: targets. Older architectures cannot run its kernels.
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