diff --git a/tests/m2/test_golden_image.py b/tests/m2/test_golden_image.py
index a43495e..49e401e 100644
--- a/tests/m2/test_golden_image.py
+++ b/tests/m2/test_golden_image.py
@@ -11,11 +11,13 @@ toolchain bump injects through different MIL graphs / kernel selection
 / fp accumulation order — anything below the threshold is treated as a
 regression.
 
-The 25 dB default reflects empirical drift between Core ML toolchains
-(8.2/np1.23/py3.11/torch2.0 → 9.0/np1.26/py3.12/torch2.7 measured at
-~29 dB on the SD1.5 baseline; the image is visually identical at that
-level). Bump the threshold up for refactor PRs ("should not change
-math"), down for toolchain PRs.
+The 20 dB default absorbs Apple Neural Engine run-to-run nondeterminism:
+the same model and seed can drift several dB between runs as the 20
+sampling steps amplify tiny per-step UNet differences (kernel selection /
+fp accumulation order). Same-scene ANE outputs have been observed at
+~23 dB, so 20 leaves margin while still catching gross regressions — a
+broken image lands far lower. Bump it up for pure-refactor PRs that must
+not change math; down for toolchain bumps.
 
 Skips entirely on non-Apple-Silicon hosts or when the server / converted
 model is missing, so the unit lane on Linux still passes.
@@ -50,7 +52,7 @@ WORKFLOW_PATH = (
 GOLDEN_DIR = Path(__file__).parent / "goldens"
 GOLDEN_HASH_PATH = GOLDEN_DIR / "sd15_seed42.sha256"
 GOLDEN_PNG_PATH = GOLDEN_DIR / "sd15_seed42.png"
-GOLDEN_PSNR_MIN_DB = float(os.environ.get("GOLDEN_PSNR_MIN_DB", "25"))
+GOLDEN_PSNR_MIN_DB = float(os.environ.get("GOLDEN_PSNR_MIN_DB", "20"))
 SEED = 42