diff --git a/src/relay/backend/compile_engine.cc b/src/relay/backend/compile_engine.cc
index 767cb6f644de..c8327de94232 100644
--- a/src/relay/backend/compile_engine.cc
+++ b/src/relay/backend/compile_engine.cc
@@ -420,8 +420,28 @@ class MakeShapeFunc : public backend::MemoizedExprTranslator<Array<te::Tensor>>
   Array<te::Tensor> VisitExpr_(const ConstantNode* op) final {
     using tir::make_const;
     ICHECK(data_dependants_.size());
-    ICHECK(op->is_scalar());
     bool data_dependant = data_dependants_.back();
+    if (!op->is_scalar()) {
+      // This is a constant weight, extract the shape of the weight tensor.
+      // This can not be data dependent.
+      CHECK(!data_dependant);
+      auto ttype = op->checked_type().as<TensorTypeNode>();
+      int ndim = static_cast<int>(ttype->shape.size());
+      Array<PrimExpr> out_shape{ndim};
+      te::Tensor value = tvm::te::compute(
+          out_shape,
+          [&](const Array<tvm::tir::Var>& indices) {
+            auto idx = indices[0];
+            PrimExpr ret = make_const(DataType::Int(64), 0);
+            for (int i = 0; i < ndim; i++) {
+              ret = tvm::if_then_else(idx == i, ttype->shape[i], ret);
+            }
+            return ret;
+          },
+          "shape_const", topi::kBroadcast);
+      scalars_.push_back(value);
+      return {value};
+    }
     if (data_dependant) {
       void* data = op->data->data;
       DataType dtype = DataType(op->data->dtype);
diff --git a/tests/python/relay/test_vm.py b/tests/python/relay/test_vm.py
index 92d6e8e55db4..6958010176e3 100644
--- a/tests/python/relay/test_vm.py
+++ b/tests/python/relay/test_vm.py
@@ -770,5 +770,30 @@ def test_vm_reshape_tuple(x_shape=(1, 4, 2), y_shape=(1, 2, 10)):
         tvm.testing.assert_allclose(res.asnumpy(), np.reshape(x_data, (1, -1)))
 
 
+def test_constant_shape_with_external_codegen():
+    mod = tvm.IRModule()
+    shape = (relay.Any(), 25)
+    dtype = "float32"
+
+    # external function
+    x = relay.var("x", shape=shape, dtype=dtype)
+    weight = relay.const(np.random.rand(5, 25).astype("float32"), dtype="float32")
+    out = relay.nn.dense(x, weight)
+    f1 = relay.Function([x], out)
+    f1 = f1.with_attr("Primitive", tvm.tir.IntImm("int32", 1))
+    f1 = f1.with_attr("Inline", tvm.tir.IntImm("int32", 1))
+    f1 = f1.with_attr("Compiler", "a")
+    glb_f1 = relay.GlobalVar("f1")
+    mod[glb_f1] = f1
+    mod = relay.transform.InferType()(mod)
+
+    # Main function
+    x = relay.var("x", shape=shape, dtype=dtype)
+    mod["main"] = relay.Function([x], glb_f1(x))
+    comp = relay.vm.VMCompiler()
+    opt_mod, _ = comp.optimize(mod, target="llvm")
+    assert "shape_func" in opt_mod.astext(False)
+
+
 if __name__ == "__main__":
     pytest.main([__file__])