diff --git a/csrc/cpu/dnnl_kernels.cpp b/csrc/cpu/dnnl_kernels.cpp
index 9a3af4ac9d8a..1c42a75bc2d6 100644
--- a/csrc/cpu/dnnl_kernels.cpp
+++ b/csrc/cpu/dnnl_kernels.cpp
@@ -523,7 +523,7 @@ void onednn_mm(torch::Tensor& c,        // [M, OC], row-major
   CPU_KERNEL_GUARD_IN(onednn_mm)
   TORCH_CHECK(a.dim() == 2);
   TORCH_CHECK(a.stride(-1) == 1);
-  TORCH_CHECK(c.is_contiguous());
+  TORCH_CHECK(c.stride(-1) == 1);
   MatMulPrimitiveHandler* ptr =
       reinterpret_cast<MatMulPrimitiveHandler*>(handler);
 
diff --git a/vllm/platforms/cpu.py b/vllm/platforms/cpu.py
index c5b6d91a62b6..544e091491bf 100644
--- a/vllm/platforms/cpu.py
+++ b/vllm/platforms/cpu.py
@@ -185,6 +185,11 @@ def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
             parallel_config.distributed_executor_backend = "mp"
         if parallel_config.worker_cls == "auto":
             parallel_config.worker_cls = "vllm.v1.worker.cpu_worker.CPUWorker"
+        # Disable DBO
+        if parallel_config.enable_dbo:
+            logger.warning(
+                "Dual-Batch Overlap is not supported on CPU, disabled.")
+            parallel_config.enable_dbo = False
 
         # Note: workaround for v1 gpu_model_runner
         from vllm.config import CompilationLevel
diff --git a/vllm/v1/worker/cpu_model_runner.py b/vllm/v1/worker/cpu_model_runner.py
index ccdbeac64bce..cd0f0af43e7e 100644
--- a/vllm/v1/worker/cpu_model_runner.py
+++ b/vllm/v1/worker/cpu_model_runner.py
@@ -145,12 +145,20 @@ def __init__(self, *args, **kwargs) -> None:
             self.record = lambda: None
             self.synchronize = lambda: None
 
+    class _StreamPlaceholder:
+
+        def __init__(self, *args, **kwargs) -> None:
+            pass
+
     cuda_event = torch.cuda.Event
+    cuda_stream = torch.cuda.Stream
     try:
         torch.cuda.Event = _EventPlaceholder
+        torch.cuda.Stream = _StreamPlaceholder
         yield
     finally:
         torch.cuda.Event = cuda_event
+        torch.cuda.Stream = cuda_stream
 
 
 @contextmanager