diff --git a/src/relay/op/tensor/transform.cc b/src/relay/op/tensor/transform.cc
index 9f9ed1c075cd..3781107eeee1 100644
--- a/src/relay/op/tensor/transform.cc
+++ b/src/relay/op/tensor/transform.cc
@@ -2829,15 +2829,18 @@ bool SplitRel(const Array<Type>& types, int num_inputs, const Attrs& attrs,
     }
     reporter->Assign(types[1], TupleType(Array<Type>(fields)));
   } else {
-    auto indices = Downcast<Array<ObjectRef>>(param->indices_or_sections);
+    Array<IndexExpr> indices;
+    for (auto i : Downcast<Array<Integer>>(param->indices_or_sections)) {
+      indices.push_back(IntImm(DataType::Int(32), i.as<IntImmNode>()->value));
+    }
     auto begin = IndexExpr(tir::make_zero(DataType::Int(32)));
     std::vector<Type> fields;
     for (unsigned int i = 0; i < indices.size(); ++i) {
-      ICHECK(reporter->Assert(Downcast<IndexExpr>(indices[i]) > begin))
+      ICHECK(reporter->Assert(indices[i] > begin))
           << "indices_or_sections need to be a sorted ascending list";
       std::vector<IndexExpr> oshape(data->shape.begin(), data->shape.end());
-      oshape[axis] = Downcast<IndexExpr>(indices[i]) - begin;
-      begin = Downcast<IndexExpr>(indices[i]);
+      oshape[axis] = indices[i] - begin;
+      begin = indices[i];
       auto vec_type = TensorType(oshape, data->dtype);
       fields.push_back(vec_type);
     }
diff --git a/tests/python/relay/test_op_level3.py b/tests/python/relay/test_op_level3.py
index 41a866a0a034..e0b95fe7fbf7 100644
--- a/tests/python/relay/test_op_level3.py
+++ b/tests/python/relay/test_op_level3.py
@@ -516,6 +516,21 @@ def verify_split(dshape, indices_or_sections, ret_type, axis=None):
         ),
         axis=1,
     )
+    verify_split(
+        (d1, d2, d3, d4),
+        tuple(np.array([2, 4, 7]).astype(np.int64)),
+        relay.ty.TupleType(
+            tvm.runtime.convert(
+                [
+                    relay.ty.TensorType((d1, 2, d3, d4), "float32"),
+                    relay.ty.TensorType((d1, 2, d3, d4), "float32"),
+                    relay.ty.TensorType((d1, 3, d3, d4), "float32"),
+                    relay.ty.TensorType((d1, (d2 - 7), d3, d4), "float32"),
+                ]
+            )
+        ),
+        axis=1,
+    )
 
 
 def test_full_infer_type():