diff --git a/openllm-python/src/openllm/_llm.py b/openllm-python/src/openllm/_llm.py
index 5993ba3a..7c10da7f 100644
--- a/openllm-python/src/openllm/_llm.py
+++ b/openllm-python/src/openllm/_llm.py
@@ -258,13 +258,15 @@ class LLM(t.Generic[M, T], ReprMixin):
       config_dtype = getattr(hf_config, 'torch_dtype', None)
       if config_dtype is None:
         config_dtype = torch.float32
-      if self.__llm_torch_dtype__ == 'auto':
+      if not torch.cuda.is_available():
+        if self.__llm_torch_dtype__ in {'auto', 'half'}:
+          logger.warning('"auto" and "half" are not supported on CPU. OpenLLM will default fallback to "float32".')
+        torch_dtype = torch.float32  # we need to cast back to full precision if cuda is not available
+      elif self.__llm_torch_dtype__ == 'auto':
         if config_dtype == torch.float32:
           torch_dtype = torch.float16  # following common practice
         else:
           torch_dtype = config_dtype
-        if not torch.cuda.is_available():
-          torch_dtype = torch.float32  # we need to cast back to full precision if cuda is not available
       else:
         if self.__llm_torch_dtype__ not in _torch_dtype_mapping():
           raise ValueError(f"Unknown dtype '{self.__llm_torch_dtype__}'")