diff --git a/python/sglang/srt/batch_overlap/two_batch_overlap.py b/python/sglang/srt/batch_overlap/two_batch_overlap.py
index d8c843485..dbec58605 100644
--- a/python/sglang/srt/batch_overlap/two_batch_overlap.py
+++ b/python/sglang/srt/batch_overlap/two_batch_overlap.py
@@ -680,6 +680,11 @@ class TboForwardBatchPreparer:
             ):
                 output_dict[key] = None
                 continue
+            elif key == "rids" and len(old_value) != num_seqs:
+                output_dict[key] = old_value[
+                    start_seq_index : min(end_seq_index, len(old_value))
+                ]
+                continue
             assert (
                 len(old_value) == num_seqs
             ), f"{key=} {old_value=} {num_seqs=} {batch=}"
diff --git a/python/sglang/srt/models/deepseek_v2.py b/python/sglang/srt/models/deepseek_v2.py
index b0c8bb870..c9e24145c 100644
--- a/python/sglang/srt/models/deepseek_v2.py
+++ b/python/sglang/srt/models/deepseek_v2.py
@@ -1339,9 +1339,7 @@ class DeepseekV2MoE(nn.Module):
             return None
 
     def op_gate(self, state):
-        if is_non_idle_and_non_empty(
-            state.forward_batch.forward_mode, state.hidden_states_mlp_input
-        ):
+        if state.hidden_states_mlp_input.shape[0] > 0:
             # router_logits: (num_tokens, n_experts)
             state.router_logits = self.gate(state.hidden_states_mlp_input)
         else:
diff --git a/python/sglang/srt/server_args.py b/python/sglang/srt/server_args.py
index b22e8f0bc..89a497bcc 100644
--- a/python/sglang/srt/server_args.py
+++ b/python/sglang/srt/server_args.py
@@ -7858,11 +7858,6 @@ class ServerArgs:
                 "When enabling two batch overlap, moe_a2a_backend cannot be 'none'."
             )
 
-        if self.enable_two_batch_overlap and self.enforce_shared_experts_fusion:
-            raise ValueError(
-                "--enable-two-batch-overlap and --enforce-shared-experts-fusion cannot be used together."
-            )
-
         # Check communications compression
         if self.enable_quant_communications and self.tp_size == 1:
             raise ValueError(
diff --git a/test/registered/ep/test_tbo_shared_experts_fusion.py b/test/registered/ep/test_tbo_shared_experts_fusion.py
new file mode 100644
index 000000000..265b436bf
--- /dev/null
+++ b/test/registered/ep/test_tbo_shared_experts_fusion.py
@@ -0,0 +1,73 @@
+import os
+import unittest
+from types import SimpleNamespace
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.ci.ci_register import register_cuda_ci
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_server,
+)
+
+register_cuda_ci(est_time=900, stage="extra-b", runner_config="deepep-8-gpu-h200")
+
+DEEPSEEK_V3_MODEL_PATH = "deepseek-ai/DeepSeek-V3-0324"
+
+
+class TestTBOWithSharedExpertsFusion(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEEPSEEK_V3_MODEL_PATH
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--trust-remote-code",
+                "--tp",
+                "8",
+                "--enable-dp-attention",
+                "--dp",
+                "8",
+                "--moe-dense-tp-size",
+                "1",
+                "--moe-a2a-backend",
+                "deepep",
+                "--enable-two-batch-overlap",
+                "--enforce-shared-experts-fusion",
+                "--disable-cuda-graph",
+                "--max-running-requests",
+                "512",
+            ],
+            env={
+                **os.environ,
+                "SGLANG_TBO_DEBUG": "1",
+            },
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="gsm8k",
+            api="completion",
+            max_tokens=512,
+            num_examples=200,
+            num_threads=128,
+        )
+        metrics = run_eval(args)
+        print(metrics)
+
+        self.assertGreater(metrics["score"], 0.60)
+
+
+if __name__ == "__main__":
+    unittest.main()