diff --git a/src/ATen/native/xpu/SummaryOps.cpp b/src/ATen/native/xpu/SummaryOps.cpp
index 0f5cbe43506..98f0d8c42ad 100644
--- a/src/ATen/native/xpu/SummaryOps.cpp
+++ b/src/ATen/native/xpu/SummaryOps.cpp
@@ -55,6 +55,13 @@ Tensor& _histc_out_xpu(
     const Scalar& min,
     const Scalar& max,
     Tensor& result) {
+  TORCH_CHECK(
+      self.dtype() == result.dtype(),
+      "torch.histogram: input tensor and hist tensor should",
+      " have the same dtype, but got input ",
+      self.dtype(),
+      " and hist ",
+      result.dtype());
   auto ret = _histc_xpu(self, bins, min, max);
   at::native::resize_output(result, ret.sizes());
   result.copy_(ret);
diff --git a/test/xpu/skip_list_common.py b/test/xpu/skip_list_common.py
index 33245852f24..8a631a1950c 100644
--- a/test/xpu/skip_list_common.py
+++ b/test/xpu/skip_list_common.py
@@ -183,7 +183,6 @@
         # Exception: The supported dtypes for linalg.multi_dot on device type xpu are incorrect!
         "test_dtypes_linalg_multi_dot_xpu",
         # For CUDA it's skipped explicitly in common_methods_invocations.py in upstream. We can skip it here
-        "test_out_histc_xpu_float32",
         "test_out_mean_xpu_float32",
         # FakeTensor mismatch in outputs_alias_inputs for aten.view.default
         # Known upstream issue: https://github.com/pytorch/pytorch/issues/159150
diff --git a/test/xpu/xpu_test_utils.py b/test/xpu/xpu_test_utils.py
index 50929bf4c38..d66b817ad13 100644
--- a/test/xpu/xpu_test_utils.py
+++ b/test/xpu/xpu_test_utils.py
@@ -349,7 +349,6 @@
     ("_batch_norm_with_update", "test_dispatch_symbolic_meta_outplace_all_strides"),
     ("_native_batch_norm_legit", "test_out"),
     ("native_batch_norm", "test_out"),
-    ("histc", "test_out"),
     ("_refs.mul", "test_python_ref"),
     ("_refs.mul", "test_python_ref_torch_fallback"),
     ("nn.AvgPool2d", "test_memory_format"),