diff --git a/python/sglang/srt/server_args.py b/python/sglang/srt/server_args.py
index 099b2df8c..845baff56 100644
--- a/python/sglang/srt/server_args.py
+++ b/python/sglang/srt/server_args.py
@@ -981,29 +981,36 @@ class ServerArgs:
 
     def _handle_deterministic_inference(self):
         if self.enable_deterministic_inference:
-            import importlib
-
-            if not importlib.util.find_spec("batch_invariant_ops"):
-                raise ValueError(
-                    "batch_invariant_ops is not installed. Please install it from https://github.com/thinking-machines-lab/batch_invariant_ops/."
-                )
-
-            # Check some settings
+            # Check sampling backend
             self.sampling_backend = "pytorch"
             logger.warning(
                 "Sampling backend is set to pytorch for deterministic inference."
             )
-            # Currently, only FA3 supports radix cache. Support for other backends is in progress
-            if self.attention_backend != "fa3":
-                self.disable_radix_cache = True
-                logger.warning(
-                    "Currently radix cache is disabled for deterministic inference. It will be supported in the future."
-                )
+
+            # Check attention backend
             if self.attention_backend not in DETERMINISTIC_ATTENTION_BACKEND_CHOICES:
                 raise ValueError(
                     f"Currently only {DETERMINISTIC_ATTENTION_BACKEND_CHOICES} attention backends are supported for deterministic inference."
                 )
 
+            # Currently, only FA3 supports radix cache. Support for other backends is in progress
+            if self.attention_backend != "fa3":
+                self.disable_radix_cache = True
+                logger.warning(
+                    f"Currently radix cache is not compatible with {self.attention_backend} attention backend for deterministic inference. It will be supported in the future."
+                )
+
+            # Check TP size
+            if self.tp_size > 1:
+                raise ValueError(
+                    "Currently only TP size 1 is supported for deterministic inference."
+                )
+
+            # Warnings on MoE models
+            logger.warning(
+                "Currently deterministic inference is only tested on dense models. Please be cautious when using it on MoE models."
+            )
+
     def _handle_other_validations(self):
         pass