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 8337d345..1aaf9e61 100644
--- a/python/llm/src/bigdl/llm/transformers/low_bit_linear.py
+++ b/python/llm/src/bigdl/llm/transformers/low_bit_linear.py
@@ -55,11 +55,9 @@ from bigdl.llm.transformers.utils import get_autocast_dtype
 T = TypeVar("T", bound="torch.nn.Module")
 
 import bigdl.llm.ggml.model.llama.llama_cpp as ggml
-from bigdl.llm.utils.isa_checker import is_server, is_spr
 import ctypes
 from bigdl.llm.ggml.quantize import ggml_tensor_qtype
-IS_SERVER = is_server()
-IS_SPR = is_spr()
+
 TORCH_LINEAR_THRESHOLD = int(os.getenv("BIGDL_LLM_LINEAR_THRESHOLD", "512"))
 SYM_INT4 = ggml_tensor_qtype["sym_int4"]
 ASYM_INT4 = ggml_tensor_qtype["asym_int4"]
@@ -518,8 +516,10 @@ class LowBitLinear(nn.Linear):
             if self.training and x.requires_grad:
                 result = MatMulLowBitCPU.apply(x, self.weight)
             else:
+                from bigdl.llm.utils.isa_checker import is_server, is_spr
+
                 # convert if necessary, and compute a linear result
-                if IS_SERVER and (not IS_SPR) and \
+                if is_server() and (not is_spr()) and \
                         self.qtype == SYM_INT4 and x_2d.shape[0] >= TORCH_LINEAR_THRESHOLD:
                     x0_fp32 = ggml_int4_convert_fp32(x0, self.weight_shape, self.weight_length)
                     result = F.linear(x, x0_fp32)
diff --git a/python/llm/src/bigdl/llm/utils/utils.py b/python/llm/src/bigdl/llm/utils/utils.py
index 1bfde572..974bf4a1 100644
--- a/python/llm/src/bigdl/llm/utils/utils.py
+++ b/python/llm/src/bigdl/llm/utils/utils.py
@@ -16,25 +16,9 @@
 
 import sys
 import pathlib
-from bigdl.llm.utils.isa_checker import check_avx_vnni, check_avx2, check_avx512_vnni
 from bigdl.llm.utils.common import invalidInputError, invalidOperationError
 
 
-def get_cpu_flags():
-    flags = ""
-    if sys.platform != "win32":
-        if check_avx512_vnni():
-            flags = "_avx512"
-        elif check_avx_vnni():
-            flags = "_avx2"
-        else:
-            invalidOperationError(False, "Unsupported CPUFLAGS.")
-    else:
-        # flags = "_vnni" if check_avx_vnni() else ""
-        flags = "-api"
-    return flags
-
-
 def get_shared_lib_info(lib_base_name: str):
     # Determine the file extension based on the platform
     if sys.platform.startswith("linux") or sys.platform == "darwin":