diff --git a/coremltools/converters/mil/mil/passes/defs/optimize_elementwise_binary.py b/coremltools/converters/mil/mil/passes/defs/optimize_elementwise_binary.py
index ddd147248..a26a0adae 100644
--- a/coremltools/converters/mil/mil/passes/defs/optimize_elementwise_binary.py
+++ b/coremltools/converters/mil/mil/passes/defs/optimize_elementwise_binary.py
@@ -39,7 +39,12 @@ def _divide_to_multiply_block(self, block):
             # to a floating point number. If x or y was originally an integer, and y becomes
             # a floating point number, then the original type
             # signature (with integer output) would not be preserved.
-            if op.op_type == "real_div" and op.y.val is not None and _types.is_float(op.x.dtype):
+            if (
+                op.op_type == "real_div"
+                and op.y.val is not None
+                and op.y.op.op_type == "const"
+                and _types.is_float(op.x.dtype)
+            ):
                 new_y_val = np.array(1.0, dtype=op.y.val.dtype) / op.y.val
                 if not np.isfinite(new_y_val).all():
                     continue
diff --git a/coremltools/converters/mil/mil/passes/tests/test_passes.py b/coremltools/converters/mil/mil/passes/tests/test_passes.py
index 668523020..ca61d2700 100644
--- a/coremltools/converters/mil/mil/passes/tests/test_passes.py
+++ b/coremltools/converters/mil/mil/passes/tests/test_passes.py
@@ -5466,6 +5466,42 @@ def prog(x):
         if _VALIDATE_MODEL:
             assert_model_is_valid(prog, {"x": (2, 4)})
 
+    def test_divide_to_multiply_skip_size(self):
+        @mb.program(input_specs=[mb.TensorSpec(shape=(42,))])
+        def prog(x):
+            div_const = mb.range_1d(start=1., end=43., step=1.)
+
+            div_val_1 = np.random.rand(42).astype(np.float32)
+            div_const_1 = mb.const(val=div_val_1)
+
+            real_div = mb.real_div(x=x, y=div_const_1)
+
+            return mb.real_div(x=real_div, y=div_const)
+
+        assert_op_count_match(prog, expect=2, op="real_div")
+        assert_op_count_match(prog, expect=0, op="mul")
+
+        def check_counts(divs, muls, const_skip=False):
+            new_prog = copy.deepcopy(prog)
+            if const_skip is None:
+                PASS_REGISTRY["common::const_elimination"](new_prog)
+            elif const_skip:
+                const_elim = copy.deepcopy(PASS_REGISTRY["common::const_elimination"])
+                const_elim.skip_const_by_size = const_skip
+                const_elim(new_prog)
+            PASS_REGISTRY["common::divide_to_multiply"](new_prog)
+            assert_same_output_names(prog, new_prog)
+            assert_op_count_match(new_prog, expect=divs, op="real_div")
+            assert_op_count_match(new_prog, expect=muls, op="mul")
+
+        check_counts(divs=1, muls=1)
+        check_counts(divs=0, muls=2, const_skip=None)
+        check_counts(divs=1, muls=1, const_skip=32)
+        check_counts(divs=0, muls=2, const_skip=64)
+
+        if _VALIDATE_MODEL:
+            assert_model_is_valid(prog, {"x": (42,)})
+
 
 class TestSelectOptimization:
     @pytest.mark.parametrize(