diff --git a/src/tir/transforms/narrow_datatype.cc b/src/tir/transforms/narrow_datatype.cc
index c2bf27393173..510093810249 100644
--- a/src/tir/transforms/narrow_datatype.cc
+++ b/src/tir/transforms/narrow_datatype.cc
@@ -107,7 +107,12 @@ class DataTypeVisitor final : public StmtExprVisitor {
       IterVar iv = Downcast<IterVar>(op->node);
       ICHECK_NE(iv->thread_tag.length(), 0U);
       analyzer_.Bind(iv->var, Range::FromMinExtent(0, op->value));
-      vextent_[iv->var.as<VarNode>()] = op->value.dtype();
+      if (op->attr_key == attr::thread_extent) {
+        // Narrow extents to 32 bits on GPU.
+        vextent_[iv->var.as<VarNode>()] = DataType::Int(32);
+      } else {
+        vextent_[iv->var.as<VarNode>()] = op->value.dtype();
+      }
       StmtExprVisitor::VisitStmt_(op);
     } else {
       StmtExprVisitor::VisitStmt_(op);
diff --git a/tests/python/relay/test_op_level10.py b/tests/python/relay/test_op_level10.py
index 0486ef40017b..85a3dd5636f1 100644
--- a/tests/python/relay/test_op_level10.py
+++ b/tests/python/relay/test_op_level10.py
@@ -229,6 +229,23 @@ def test_broadcast_to():
             tvm.testing.assert_allclose(op_res.numpy(), ref_res, rtol=1e-5)
 
 
+@tvm.testing.uses_gpu
+def test_broadcast_to_const_shape_int64():
+    shape_like = relay.const(np.array([1, 5]), dtype="int64")
+    x = relay.var("x", shape=(1,), dtype="int64")
+    z = relay.broadcast_to(x, shape=shape_like)
+    z = relay.sum(z, axis=0)
+
+    f = relay.Function([x], z)
+
+    x = np.random.randint(10, size=(1,), dtype="int64")
+    ref_res = np.broadcast_to(x, (5,))
+    for target, dev in tvm.testing.enabled_targets():
+        for kind in ["graph", "debug"]:
+            op_res = relay.create_executor(kind, device=dev, target=target).evaluate(f)(x)
+            tvm.testing.assert_allclose(op_res.numpy(), ref_res)
+
+
 @tvm.testing.uses_gpu
 def test_broadcast_to_like():
     shape = (4, 1, 6)