diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index 1c544d309717b..62396d839dc9b 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -822,13 +822,11 @@ class Prelu(OnnxOpConverter):
     @classmethod
     def _impl_v1(cls, inputs, attr, params):
         assert len(inputs) == 2, "Prelu need 2 inputs, {} given".format(len(inputs))
-        input_channels = infer_shape(inputs[0])[1]
-        alpha_shape = infer_shape(inputs[1])
-        if len(alpha_shape) != 1:
-            alpha = _op.reshape(inputs[1], (-1,))
-        else:
-            alpha = inputs[1]
-        return _op.nn.prelu(inputs[0], _op.broadcast_to(alpha, [input_channels]))
+        input_shape = _op.shape_of(inputs[0])
+        alpha = _op.broadcast_to_like(inputs[1], inputs[0])
+        alpha = _op.reshape(alpha, [-1])
+        output = _op.nn.prelu(_op.reshape(inputs[0], [-1]), alpha, axis=0)
+        return _op.reshape(output, input_shape)
 
 
 class Reciprocal(OnnxOpConverter):
diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index 3d95a9a83ee31..0f7fda7301cda 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -2037,12 +2037,15 @@ def verify_prelu(x_shape, a_shape):
 
         model = helper.make_model(graph, producer_name="prelu_test")
 
-        verify_with_ort(model, [x_shape, a_shape], list(x_shape))
+        verify_with_ort(
+            model, [x_shape, a_shape], list(x_shape), use_vm=True, convert_to_static=True
+        )
 
     verify_prelu([3, 4, 5, 6], [1, 4, 1, 1])
     verify_prelu([1, 8, 5, 6], [1, 8, 1, 1])
     verify_prelu([2, 12, 16, 16], [1, 12, 1, 1])
     verify_prelu([2, 12, 16, 16], [1])  # Test alpha broadcasting.
+    verify_prelu([3, 1], [3, 1])  # Test non NCHW workload.
 
 
 @tvm.testing.uses_gpu