diff --git a/python/sglang/srt/models/nemotron_h.py b/python/sglang/srt/models/nemotron_h.py
index e5c6f98b4..841f3d14a 100644
--- a/python/sglang/srt/models/nemotron_h.py
+++ b/python/sglang/srt/models/nemotron_h.py
@@ -55,7 +55,10 @@ from sglang.srt.layers.logits_processor import LogitsProcessor
 from sglang.srt.layers.moe.ep_moe.layer import get_moe_impl_class
 from sglang.srt.layers.moe.fused_moe_triton.layer import FusedMoE
 from sglang.srt.layers.moe.topk import TopK
-from sglang.srt.layers.moe.utils import RoutingMethodType
+from sglang.srt.layers.moe.utils import (
+    RoutingMethodType,
+    should_skip_post_experts_all_reduce,
+)
 from sglang.srt.layers.quantization import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.layers.utils import PPMissingLayer, get_layer_id
@@ -129,10 +132,10 @@ class NemotronHMLP(nn.Module):
         )
         self.act_fn = ReLU2()
 
-    def forward(self, x: torch.Tensor):
+    def forward(self, x: torch.Tensor, use_reduce_scatter: bool = False):
         x, _ = self.up_proj(x)
         x = self.act_fn(x)
-        x, _ = self.down_proj(x)
+        x, _ = self.down_proj(x, skip_all_reduce=use_reduce_scatter)
         return x
 
 
@@ -296,7 +299,9 @@ class NemotronHMoE(nn.Module):
 
         return final_hidden_states, shared_output
 
-    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
+    def forward(
+        self, hidden_states: torch.Tensor, use_reduce_scatter: bool = False
+    ) -> torch.Tensor:
         num_tokens, hidden_dim = hidden_states.shape
         # routed_scaling_factor is fused into the experts call (applied by the
         # MoE runner / topk), so final_hidden_states is already scaled.
@@ -308,7 +313,10 @@ class NemotronHMoE(nn.Module):
         if shared_output is not None:
             final_hidden_states += shared_output
 
-        if self.tp_size > 1:
+        if self.tp_size > 1 and not should_skip_post_experts_all_reduce(
+            is_tp_path=True,
+            use_reduce_scatter=use_reduce_scatter,
+        ):
             final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
 
         return final_hidden_states.view(num_tokens, hidden_dim)
@@ -328,7 +336,12 @@ class NemotronHMLPLikeDecoderLayer(nn.Module):
             hidden_states, residual = self.layer_communicator.prepare_mlp(
                 hidden_states, residual, forward_batch
             )
-            hidden_states = self.mixer.forward(hidden_states)
+            use_reduce_scatter = self.layer_communicator.should_use_reduce_scatter(
+                forward_batch
+            )
+            hidden_states = self.mixer.forward(
+                hidden_states, use_reduce_scatter=use_reduce_scatter
+            )
             hidden_states, residual = self.layer_communicator.postprocess_layer(
                 hidden_states, residual, forward_batch
             )
@@ -375,7 +388,9 @@ class NemotronHMLPDecoderLayer(NemotronHMLPLikeDecoderLayer):
         )
 
         self.norm = RMSNorm(config.hidden_size, eps=config.layer_norm_epsilon)
-        self.layer_communicator = make_layer_communicator(self.norm, for_attn=False)
+        self.layer_communicator = make_layer_communicator(
+            self.norm, for_attn=False, allow_reduce_scatter=True
+        )
 
 
 class NemotronHMoEDecoderLayer(NemotronHMLPLikeDecoderLayer):
@@ -398,7 +413,9 @@ class NemotronHMoEDecoderLayer(NemotronHMLPLikeDecoderLayer):
         )
 
         self.norm = RMSNorm(config.hidden_size, eps=config.layer_norm_epsilon)
-        self.layer_communicator = make_layer_communicator(self.norm, for_attn=False)
+        self.layer_communicator = make_layer_communicator(
+            self.norm, for_attn=False, allow_reduce_scatter=True
+        )
 
 
 class NemotronHAttnLikeDecoderLayer(nn.Module):
diff --git a/python/sglang/srt/models/nemotron_h_utils.py b/python/sglang/srt/models/nemotron_h_utils.py
index 9c63a26d7..057128c66 100644
--- a/python/sglang/srt/models/nemotron_h_utils.py
+++ b/python/sglang/srt/models/nemotron_h_utils.py
@@ -57,11 +57,12 @@ def _build_layer_scatter_modes() -> LayerScatterModes:
 
 
 def make_layer_communicator(
-    layer_norm: RMSNorm, *, for_attn: bool
+    layer_norm: RMSNorm, *, for_attn: bool, allow_reduce_scatter: bool = False
 ) -> LayerCommunicator:
     return LayerCommunicator(
         layer_scatter_modes=_build_layer_scatter_modes(),
         input_layernorm=layer_norm if for_attn else nn.Identity(),
         post_attention_layernorm=nn.Identity() if for_attn else layer_norm,
         force_layernorm_before_dp_gather=True,
+        allow_reduce_scatter=allow_reduce_scatter,
     )