diff --git a/coremltools/optimize/coreml/_quantization_passes.py b/coremltools/optimize/coreml/_quantization_passes.py
index 849e2fe34..53ca42a2f 100644
--- a/coremltools/optimize/coreml/_quantization_passes.py
+++ b/coremltools/optimize/coreml/_quantization_passes.py
@@ -1139,12 +1139,28 @@ def transform_op(self, op: Operation):
                         "Palettization with per-channel-scale is only supported since "
                         "iOS18. Please set minimum_deployment_target accordingly."
                     )
-                new_var = mb.constexpr_blockwise_shift_scale(
-                    data=new_var,
-                    scale=per_channel_scale,
-                    offset=None,
-                    before_op=op,
+                # Bake per_channel_scale into the LUT entries instead of
+                # wrapping the dense weight in a runtime
+                # constexpr_blockwise_shift_scale: that wrapper fails MPSGraph
+                # verification on Apple Neural Engine (macOS 26+) because the
+                # mps.dequantize lowering expects an integer data operand.
+                # Folding is mathematically identical (output = data * scale).
+                lut = lut_params.lut.copy()
+                # LUT has trailing dims [group, num_palette, vector_size] that
+                # are not present in per_channel_scale; broadcast across those.
+                pcs_bcast = per_channel_scale.reshape(
+                    per_channel_scale.shape
+                    + (1,) * (lut.ndim - per_channel_scale.ndim)
+                )
+                lut = (
+                    lut.astype(np.float32) * pcs_bcast.astype(np.float32)
+                ).astype(lut.dtype)
+                new_var = frontend_utils._construct_constexpr_lut_op(
+                    lut_params.indices,
+                    lut,
+                    lut_params.vector_axis,
                     name=op.name + "_palettized_pcs",
+                    before_op=op,
                 )
         else:
             decompressed_val = self.decompress(lut_params)
diff --git a/coremltools/test/optimize/coreml/test_post_training_quantization.py b/coremltools/test/optimize/coreml/test_post_training_quantization.py
index 37148aba6..4478eb993 100644
--- a/coremltools/test/optimize/coreml/test_post_training_quantization.py
+++ b/coremltools/test/optimize/coreml/test_post_training_quantization.py
@@ -1683,13 +1683,13 @@ def test_palettization_pcs(self, compute_unit, backend):
             op_type="constexpr_lut_to_dense"
         )[0]
         assert types.builtin_to_string(palettize_op.indices.dtype) == "uint4"
-        # The per-channel-scale is represented by a quant op to do scaling.
+        # per_channel_scale is folded into the LUT entries at compile time, so
+        # no runtime constexpr_blockwise_shift_scale wrapper is emitted (see
+        # palettize_weights in _quantization_passes.py for the rationale).
         quantize_ops = mlmodel_palettized._mil_program.functions["main"].find_ops(
             op_type="constexpr_blockwise_shift_scale"
         )
-        assert len(quantize_ops) > 0
-        # Order of quant and lut op is determined by canonicalize_quantized_lut_pattern graph pass.
-        assert quantize_ops[0].outputs[0].child_ops[0].op_type == "constexpr_lut_to_dense"
+        assert len(quantize_ops) == 0
 
         if _macos_version() >= (15, 0):
             verify_model_outputs(mlmodel, mlmodel_palettized, coreml_input_values)