diff --git a/python/llm/src/bigdl/llm/transformers/low_bit_linear.py b/python/llm/src/bigdl/llm/transformers/low_bit_linear.py
index 51231275..27e1e44c 100644
--- a/python/llm/src/bigdl/llm/transformers/low_bit_linear.py
+++ b/python/llm/src/bigdl/llm/transformers/low_bit_linear.py
@@ -60,6 +60,7 @@ IS_SERVER = is_server()
 IS_SPR = is_spr()
 TORCH_LINEAR_THRESHOLD = 96
 SYM_INT4 = ggml_tensor_qtype["sym_int4"]
+SYM_INT8 = ggml_tensor_qtype["sym_int8"]
 
 
 def ggml_convert_qtype(tensor: torch.Tensor, qtype: int, device=None):
@@ -98,7 +99,7 @@ def ggml_q_format_convet_cpu2xpu(tensor: torch.Tensor, num_elem: int, qtype: int
 
     src = ctypes.c_void_p(tensor.data.data_ptr())
 
-    if qtype == ggml_tensor_qtype["sym_int4"]:
+    if qtype in [SYM_INT4, SYM_INT8]:
         dst_tensor = torch.empty_like(tensor)
     elif qtype == ggml_tensor_qtype["sym_int5"]:
         QK = ggml.ggml_qk_size(qtype)
@@ -123,7 +124,7 @@ def ggml_q_format_convet_xpu2cpu(tensor: torch.Tensor, num_elem: int, qtype: int
 
     src = ctypes.c_void_p(tensor.data.data_ptr())
 
-    if qtype == ggml_tensor_qtype["sym_int4"]:
+    if qtype in [SYM_INT4, SYM_INT8]:
         dst_tensor = torch.empty_like(tensor)
     elif qtype == ggml_tensor_qtype["sym_int5"]:
         QK = ggml.ggml_qk_size(ggml_tensor_qtype["asym_int5"])