diff --git a/scripts/probe-fft-platform.py b/scripts/probe-fft-platform.py
new file mode 100644
index 00000000..57707280
--- /dev/null
+++ b/scripts/probe-fft-platform.py
@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+"""Platform probe: reproduce verify.py's hash-relevant FFT steps in isolation.
+
+Runs the same scipy.fft.fft / scipy.signal calls that verify.py hashes
+(csi_processor.py:426, :438, :349) on a deterministic synthetic input,
+without dragging in src.app / pydantic Settings. Used to empirically
+locate the source of platform divergence in issue #560.
+
+Usage:  python3 scripts/probe-fft-platform.py
+Output: single JSON object on stdout. Run on each platform and diff.
+
+If two machines print the same `first8_doppler_bytes_hex` and the same
+`first4_psd_floats` but different `sha256`, the divergence is in later
+FFT bins (SIMD reordering). If even the first values differ, it's a
+true ULP-level divergence at every bin (Apple Silicon NEON vs x86_64
+AVX, or different scipy pocketfft builds).
+"""
+import hashlib
+import json
+import platform
+import struct
+import sys
+
+import numpy as np
+import scipy.fft
+import scipy.signal
+
+# Deterministic synthetic input -- no IO, no .env, no Settings
+rng = np.random.RandomState(42)
+N_FRAMES = 100
+N_SUBC = 100
+amp = rng.randn(N_FRAMES, N_SUBC).astype(np.float64)
+
+# Mirror the three scipy calls verify.py's hash depends on:
+#   archive/v1/src/core/csi_processor.py:349 -> scipy.signal.windows.hamming
+#   archive/v1/src/core/csi_processor.py:426 -> scipy.fft.fft(mean_phase_diff, n=64)
+#   archive/v1/src/core/csi_processor.py:438 -> scipy.fft.fft(amp.flatten(), n=128)
+mean_phase_diff = amp.mean(axis=1)
+doppler = np.abs(scipy.fft.fft(mean_phase_diff, n=64)) ** 2
+psd = np.abs(scipy.fft.fft(amp.flatten(), n=128)) ** 2
+window = scipy.signal.windows.hamming(56)
+
+# Pack the same way verify.py:features_to_bytes does (little-endian f64)
+parts = []
+for arr in (doppler, psd, window):
+    flat = np.asarray(arr, dtype=np.float64).ravel()
+    parts.append(struct.pack(f"<{len(flat)}d", *flat))
+blob = b"".join(parts)
+
+try:
+    blas_info = np.show_config(mode="dicts")
+except Exception:
+    blas_info = {"error": "show_config(mode=dicts) unavailable"}
+
+print(json.dumps({
+    "uname": platform.uname()._asdict(),
+    "python": sys.version.split()[0],
+    "numpy": np.__version__,
+    "scipy": __import__("scipy").__version__,
+    "blob_len": len(blob),
+    "sha256": hashlib.sha256(blob).hexdigest(),
+    "first8_doppler_bytes_hex": doppler[:8].tobytes().hex(),
+    "first4_psd_floats": psd[:4].tolist(),
+    "blas_backend": blas_info if isinstance(blas_info, dict) else str(blas_info),
+}, indent=2, default=str))