diff --git a/optimum/quanto/library/qbytes_mm.py b/optimum/quanto/library/qbytes_mm.py
index 62da6f2e..22319345 100644
--- a/optimum/quanto/library/qbytes_mm.py
+++ b/optimum/quanto/library/qbytes_mm.py
@@ -92,7 +92,7 @@ def qbytes_mm_impl_cuda(activations: torch.Tensor, weights: torch.Tensor, output
 def qbytes_mm_impl_cpu(activations: torch.Tensor, weights: torch.Tensor, output_scales: torch.Tensor) -> torch.Tensor:
     if (
         # FIXME: accuracy issues with 2.4.x
-        version.parse(torch.__version__).release > version.parse("2.5.0").release
+        version.parse(torch.__version__).release >= version.parse("2.6.0").release
         and activations.dtype == torch.int8
         and weights.dtype == torch.int8
     ):
diff --git a/test/conftest.py b/test/conftest.py
index d8bb234c..5e9b4367 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -21,6 +21,8 @@
     devices += ["cuda"]
 elif torch.backends.mps.is_available():
     devices += ["mps"]
+elif torch.xpu.is_available():
+    devices += ["xpu"]
 
 
 @pytest.fixture(scope="module", params=devices)
diff --git a/test/helpers.py b/test/helpers.py
index 1693d6a9..3e6635f3 100644
--- a/test/helpers.py
+++ b/test/helpers.py
@@ -103,6 +103,9 @@ def get_device_memory(device):
     elif device.type == "mps":
         torch.mps.empty_cache()
         return torch.mps.current_allocated_memory()
+    elif device.type == "xpu":
+        torch.xpu.empty_cache()
+        return torch.xpu.memory_allocated()
     return None
 
 
diff --git a/test/tensor/weights/weight_helpers.py b/test/tensor/weights/weight_helpers.py
index 761cbea3..762836e7 100644
--- a/test/tensor/weights/weight_helpers.py
+++ b/test/tensor/weights/weight_helpers.py
@@ -31,7 +31,7 @@ def check_weight_qtensor_linear(qweight, batch_size, tokens, use_bias, rel_max_e
     max_err = (out - qout).abs().max()
     rel_max_err = max_err / mean_val
     # These values were evaluated empirically without any optimized kernels.
-    rtol = {"cpu": 1e-2, "cuda": 2e-2, "mps": 1e-2}[device.type]
+    rtol = {"cpu": 1e-2, "cuda": 2e-2, "mps": 1e-2, "xpu": 2e-2}[device.type]
     assert (
         rel_max_err < rtol
     ), f"Maximum error {max_err:.2f} is too high for input of mean value {mean_val:.2f} ({rel_max_err*100:.2f} %)"