diff --git a/src/relay/op/contrib/ethosu/depthwise.cc b/src/relay/op/contrib/ethosu/depthwise.cc
index fa73645d45de..b102ce26c912 100644
--- a/src/relay/op/contrib/ethosu/depthwise.cc
+++ b/src/relay/op/contrib/ethosu/depthwise.cc
@@ -126,7 +126,7 @@ bool EthosuDepthwiseConv2DRel(const Array<Type>& types, int num_inputs, const At
   ICHECK(ifm->dtype == DataType::UInt(8) || ifm->dtype == DataType::Int(8))
       << "Expected ethosu_depthwise_conv2d type(uint8) or type(int8) for ifm but was "
       << ifm->dtype;
-  ICHECK(weight->dtype == DataType::UInt(8) || ifm->dtype == DataType::Int(8))
+  ICHECK(weight->dtype == DataType::UInt(8) || weight->dtype == DataType::Int(8))
       << "Expected ethosu_depthwise_conv2d type(uint8) or type(int8) for weight but was "
       << weight->dtype;
   ICHECK(scale_bias->dtype == DataType::UInt(8))
diff --git a/tests/python/contrib/test_ethosu/test_replace_depthwise_conv2d.py b/tests/python/contrib/test_ethosu/test_replace_depthwise_conv2d.py
index b3ce74c4e84a..93a2f9e133ce 100644
--- a/tests/python/contrib/test_ethosu/test_replace_depthwise_conv2d.py
+++ b/tests/python/contrib/test_ethosu/test_replace_depthwise_conv2d.py
@@ -23,22 +23,83 @@
 from tvm import relay
 from tvm.relay.testing import run_opt_pass
 from tvm.relay.backend.contrib.ethosu.tir.compiler import lower_to_tir
+
 from .infra import make_ethosu_depthwise_conv2d, get_convolutional_args
 
 
 @pytest.mark.parametrize(
     "trial",
     [
-        [(1, 8, 8, 3), 3, (3, 2), (0, 0), (1, 1), (1, 1), "CLIP", "NHWC", "NHWC"],
-        [(1, 8, 8, 3), 3, (1, 1), (2, 1), (1, 1), (1, 1), "TANH", "NHWC", "NHWC"],
-        [(1, 8, 8, 3), 3, (1, 1), (0, 0), (1, 1), (1, 1), "NONE", "NHWC", "NHWC"],
-        [(1, 1, 1, 1), 1, (1, 1), (0, 0), (1, 1), (1, 1), "CLIP", "NHWC", "NHWC"],
-        [(1, 7, 9, 4), 4, (3, 2), (1, 2), (2, 1), (1, 2), "SIGMOID", "NHWC", "NHWC"],
-        [(1, 8, 2, 8, 16), 18, (1, 1), (2, 1), (1, 1), (1, 1), "CLIP", "NHCWB16", "NHWC"],
-        [(1, 7, 9, 40), 40, (3, 2), (1, 2), (2, 1), (1, 2), "CLIP", "NHWC", "NHCWB16"],
-        [(1, 4, 12, 9, 16), 182, (2, 3), (6, 3), (2, 2), (1, 1), "CLIP", "NHCWB16", "NHCWB16"],
-        [(1, 7, 9, 4), 4, (3, 2), (1, 2), (2, 1), (2, 2), "CLIP", "NHWC", "NHWC"],
-        [(1, 7, 9, 41), 41, (3, 2), (1, 2), (2, 1), (2, 2), "CLIP", "NHWC", "NHCWB16"],
+        [(1, 8, 8, 3), 3, (3, 2), (0, 0), (1, 1), (1, 1), "CLIP", "NHWC", "NHWC", "int8", "int8"],
+        [(1, 8, 8, 3), 3, (1, 1), (2, 1), (1, 1), (1, 1), "TANH", "NHWC", "NHWC", "int8", "int8"],
+        [(1, 8, 8, 3), 3, (1, 1), (0, 0), (1, 1), (1, 1), "NONE", "NHWC", "NHWC", "uint8", "int8"],
+        [(1, 1, 1, 1), 1, (1, 1), (0, 0), (1, 1), (1, 1), "CLIP", "NHWC", "NHWC", "uint8", "int8"],
+        [
+            (1, 7, 9, 4),
+            4,
+            (3, 2),
+            (1, 2),
+            (2, 1),
+            (1, 2),
+            "SIGMOID",
+            "NHWC",
+            "NHWC",
+            "uint8",
+            "uint8",
+        ],
+        [
+            (1, 8, 2, 8, 16),
+            18,
+            (1, 1),
+            (2, 1),
+            (1, 1),
+            (1, 1),
+            "CLIP",
+            "NHCWB16",
+            "NHWC",
+            "int8",
+            "int8",
+        ],
+        [
+            (1, 7, 9, 40),
+            40,
+            (3, 2),
+            (1, 2),
+            (2, 1),
+            (1, 2),
+            "CLIP",
+            "NHWC",
+            "NHCWB16",
+            "int8",
+            "int8",
+        ],
+        [
+            (1, 4, 12, 9, 16),
+            182,
+            (2, 3),
+            (6, 3),
+            (2, 2),
+            (1, 1),
+            "CLIP",
+            "NHCWB16",
+            "NHCWB16",
+            "int8",
+            "int8",
+        ],
+        [(1, 7, 9, 4), 4, (3, 2), (1, 2), (2, 1), (2, 2), "CLIP", "NHWC", "NHWC", "int8", "int8"],
+        [
+            (1, 7, 9, 41),
+            41,
+            (3, 2),
+            (1, 2),
+            (2, 1),
+            (2, 2),
+            "CLIP",
+            "NHWC",
+            "NHCWB16",
+            "int8",
+            "int8",
+        ],
         [
             (1, 13, 12, 19, 16),
             182,
@@ -49,6 +110,8 @@
             "CLIP",
             "NHCWB16",
             "NHCWB16",
+            "int8",
+            "int8",
         ],
     ],
 )
@@ -63,8 +126,10 @@ def _get_func(
         activation,
         ifm_layout,
         ofm_layout,
+        dtype,
+        weight_dtype,
     ):
-        ifm = relay.var("ifm", shape=ifm_shape, dtype="int8")
+        ifm = relay.var("ifm", shape=ifm_shape, dtype=dtype)
         depthwise = make_ethosu_depthwise_conv2d(
             ifm,
             channels,
@@ -75,6 +140,7 @@ def _get_func(
             activation,
             ifm_layout,
             ofm_layout,
+            weight_dtype,
         )
         func = relay.Function(relay.analysis.free_vars(depthwise), depthwise)
         func = run_opt_pass(func, relay.transform.InferType())
@@ -99,6 +165,8 @@ def _visit(stmt):
         activation,
         ifm_layout,
         ofm_layout,
+        dtype,
+        _,
     ) = trial
     dilated_kernel_h = (kernel_shape[0] - 1) * dilation[0] + 1
     dilated_kernel_w = (kernel_shape[1] - 1) * dilation[1] + 1
@@ -125,7 +193,7 @@ def _visit(stmt):
         ofm_stride_h = 16 * ofm_width * ((channels - 1) // 16 + 1)
 
     answer = [
-        "int8",
+        dtype,
         ifm_shape[1],
         ifm_shape[2] if ifm_layout == "NHWC" else ifm_shape[3],
         channels,
@@ -142,7 +210,7 @@ def _visit(stmt):
         ifm_stride_h,
         ifm_stride_w,
         ifm_stride_c,
-        "int8",
+        dtype,
         ofm_height,
         ofm_width,
         channels,
diff --git a/tests/python/contrib/test_ethosu/test_type_inference.py b/tests/python/contrib/test_ethosu/test_type_inference.py
index 47fddad773b2..681c49eb68ba 100644
--- a/tests/python/contrib/test_ethosu/test_type_inference.py
+++ b/tests/python/contrib/test_ethosu/test_type_inference.py
@@ -18,7 +18,7 @@
 
 pytest.importorskip("ethosu.vela")
 
-from tvm import relay
+from tvm import relay, TVMError
 from tvm.relay.testing import run_opt_pass
 from .infra import make_ethosu_conv2d
 from .infra import make_ethosu_depthwise_conv2d
@@ -92,5 +92,29 @@ def test_ethosu_depthwise_conv2d_type_inference(
     assert tuple(f.body.checked_type.shape) == ofm_shape
 
 
+def test_incompatible_weight_data_type():
+    ifm = relay.var("ifm", shape=(1, 8, 8, 3), dtype="int8")
+    depthwise = make_ethosu_depthwise_conv2d(
+        ifm=ifm,
+        channels=3,
+        kernel_shape=(3, 2),
+        padding=(0, 0),
+        strides=(1, 1),
+        dilation=(1, 1),
+        activation="NONE",
+        ifm_layout="NHWC",
+        ofm_layout="NHWC",
+        weight_dtype="int16",
+    )
+
+    func = relay.Function(relay.analysis.free_vars(depthwise), depthwise)
+
+    message = (
+        r"Expected ethosu_depthwise_conv2d type\(uint8\) or type\(int8\) for weight but was int16"
+    )
+    with pytest.raises(TVMError, match=message):
+        run_opt_pass(func, relay.transform.InferType())
+
+
 if __name__ == "__main__":
     pytest.main([__file__])