diff --git a/src/relay/op/nn/nn.h b/src/relay/op/nn/nn.h
index f5497a4603bf..cf601ff5f11b 100644
--- a/src/relay/op/nn/nn.h
+++ b/src/relay/op/nn/nn.h
@@ -113,23 +113,32 @@ bool MatmulRel(const Array<Type>& types, int num_inputs, const Attrs& attrs,
         std::vector<PrimExpr> B_shape(tensor_b->shape.begin(), tensor_b->shape.end());
         auto sa = A_shape.size();
         auto sb = B_shape.size();
+        size_t index_swap_A;
+        size_t index_swap_B;
         if (transpose_a && transpose_b) {
-          auto tmp = A_shape[sa - 2];
-          A_shape[sa - 2] = B_shape[sb - 1];
-          B_shape[sb - 1] = tmp;
+          index_swap_A = sa - 2;
+          index_swap_B = sb - 1;
         } else if (transpose_a) {
-          auto tmp = A_shape[sa - 2];
-          A_shape[sa - 2] = B_shape[sb - 2];
-          B_shape[sb - 2] = tmp;
+          index_swap_A = sa - 2;
+          index_swap_B = sb - 2;
         } else if (transpose_b) {
-          auto tmp = A_shape[sa - 1];
-          A_shape[sa - 1] = B_shape[sb - 1];
-          B_shape[sb - 1] = tmp;
+          index_swap_A = sa - 1;
+          index_swap_B = sb - 1;
         } else {
-          auto tmp = A_shape[sa - 1];
-          A_shape[sa - 1] = B_shape[sb - 2];
-          B_shape[sb - 2] = tmp;
+          index_swap_A = sa - 1;
+          index_swap_B = sb - 2;
         }
+
+        // Rewrite dynamic axes to static where constraints allow.
+        auto tmp = A_shape[index_swap_A];
+        if (A_shape[index_swap_A].as<tir::AnyNode>()) {
+          A_shape[index_swap_A] = B_shape[index_swap_B];
+        }
+        if (B_shape[index_swap_B].as<tir::AnyNode>()) {
+          B_shape[index_swap_B] = tmp;
+        }
+
+        // Update input types with new constrained shapes.
         reporter->Assign(types[0], TensorType(A_shape, tensor_a->dtype));
         reporter->Assign(types[1], TensorType(B_shape, tensor_b_dtype));
       }
diff --git a/tests/python/relay/test_op_level1.py b/tests/python/relay/test_op_level1.py
index 30d9d88ad7cb..bd4e1b72c3cd 100644
--- a/tests/python/relay/test_op_level1.py
+++ b/tests/python/relay/test_op_level1.py
@@ -25,6 +25,7 @@
 import tvm.topi.testing
 from tvm.contrib.nvcc import have_fp16
 import tvm.testing
+from tvm.topi.utils import get_const_tuple
 
 executor_kind = tvm.testing.parameter("graph", "vm")
 
@@ -695,6 +696,8 @@ def test_dense(executor_kind):
         w = relay.var("w", relay.TensorType((k, n), dtype))
         y = relay.nn.dense(x, w)
         yy = run_infer_type(y)
+        # Confirm that input shape has not been rewritten to become dynamic.
+        assert get_const_tuple(yy.type_args[0].shape) == (4, 2)
 
         n, c, h, w = te.size_var("n"), te.size_var("c"), te.size_var("h"), 2
         x = relay.var("x", relay.TensorType((n, c, h, w), dtype))