diff --git a/backends/arm/test/ops/test_slice.py b/backends/arm/test/ops/test_slice.py
index 7e71a51899a..bdf5ccda770 100644
--- a/backends/arm/test/ops/test_slice.py
+++ b/backends/arm/test/ops/test_slice.py
@@ -7,6 +7,7 @@
 
 from typing import Tuple
 
+import pytest
 import torch
 from executorch.backends.arm.quantizer.arm_quantizer import (
     get_symmetric_a16w8_quantization_config,
@@ -43,7 +44,6 @@
 
 
 class Slice(torch.nn.Module):
-
     def forward(self, x: torch.Tensor, s: list[tuple[int, int]]):
         slices = [slice(*i) for i in s]
         return x[slices]
@@ -153,6 +153,9 @@ def get_symmetric_a16w8_slice_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", test_data_suite)
+@pytest.mark.xfail(
+    reason="missing int16 slice ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13976"
+)
 def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -178,6 +181,9 @@ def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone300
+@pytest.mark.xfail(
+    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
+)
 def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -202,6 +208,9 @@ def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
+@pytest.mark.xfail(
+    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
+)
 def test_slice_tensor_16a8w_u85_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False