diff --git a/src/relay/op/tensor/transform.cc b/src/relay/op/tensor/transform.cc
index 9427dedfe3fa2..310ba20685fca 100644
--- a/src/relay/op/tensor/transform.cc
+++ b/src/relay/op/tensor/transform.cc
@@ -26,6 +26,7 @@
 #include <tvm/ir/error.h>
 #include <tvm/relay/attrs/transform.h>
 #include <tvm/relay/op.h>
+#include <tvm/relay/expr.h>
 #include <tvm/runtime/packed_func.h>
 #include <tvm/tir/data_layout.h>
 #include <tvm/tir/expr.h>
@@ -581,6 +582,29 @@ bool ReshapeRel(const Array<Type>& types, int num_inputs, const Attrs& attrs,
     oshape.Set(infer_idx, infer_dim);
   }
 
+  // Verify that the sum of dimensions in the output shape is the sum of
+  // dimensions in the input shape
+  bool found_dynamic = false;
+  int64_t oshape_sum = 1;
+  for(auto& x: oshape) {
+    if (x.as<AnyNode>() != nullptr) {
+      found_dynamic = true;
+      break;
+    }
+    oshape_sum *= Downcast<tvm::Integer>(x)->value;
+  }
+  int64_t data_shape_sum = 1;
+  for(auto& x: data_shape) {
+    if (x.as<AnyNode>() != nullptr) {
+      found_dynamic = true;
+      break;
+    }
+    data_shape_sum *= Downcast<tvm::Integer>(x)->value;
+  }
+  if (!found_dynamic) {
+    CHECK_EQ(oshape_sum, data_shape_sum) << "Input tensor shape and reshaped shape are not compatible";
+  }
+
   if (param->reverse) {
     reporter->Assign(types[1],
                      TensorType(Array<IndexExpr>(oshape.rbegin(), oshape.rend()), data->dtype));
diff --git a/tests/python/relay/test_op_level3.py b/tests/python/relay/test_op_level3.py
index 76f10d6c1a182..db45fcbef6cbf 100644
--- a/tests/python/relay/test_op_level3.py
+++ b/tests/python/relay/test_op_level3.py
@@ -21,6 +21,7 @@
 import tvm
 from tvm import te
 from tvm import relay
+from tvm.error import TVMError
 from tvm.relay import create_executor, transform
 from tvm.relay.testing import ctx_list, check_grad, run_infer_type
 
@@ -282,6 +283,13 @@ def verify_reshape(shape, newshape, oshape):
     verify_reshape((2, 3, 4), (2, -4, -1, 3, -2), (2, 1, 3, 4))
 
 
+def test_reshape_fail():
+    with pytest.raises(TVMError) as reshape_err:
+        x = relay.var("x", relay.TensorType([2,3], "float32"))
+        z = relay.reshape(x, [7])
+        zz = run_infer_type(z)
+
+
 def test_reshape_like_infer_type():
     # concrete shape
     x = relay.var("x", relay.TensorType((1, 2, 3), "float32"))
@@ -1070,6 +1078,7 @@ def verify_sparse_to_dense(sparse_indices, sparse_values, default_value, output_
     test_transpose()
     test_reshape_infer_type()
     test_reshape()
+    test_reshape_fail()
     test_reshape_like_infer_type()
     test_reshape_like()
     test_take_infer_type()