diff --git a/tensorrt_llm/_torch/models/modeling_llama.py b/tensorrt_llm/_torch/models/modeling_llama.py
index 713917f2168..2b988000374 100644
--- a/tensorrt_llm/_torch/models/modeling_llama.py
+++ b/tensorrt_llm/_torch/models/modeling_llama.py
@@ -419,11 +419,12 @@ def __init__(
                 overridden_tp_size=1 if self.enable_attention_dp else None,
                 layer_idx=layer_idx,
             )
-
+            # TODO(TRTLLM-7809): Fix fusion with PP>1
             self.fusion_config.PRE_MLP_FUSION = model_config.mapping.has_tp(
-            ) and not self.enable_attention_dp and self.enable_fusion
-            self.fusion_config.POST_MLP_FUSION = model_config.mapping.has_tp(
-            ) and not self.enable_attention_dp and self.enable_fusion
+            ) and not self.enable_attention_dp and self.enable_fusion and not model_config.mapping.has_pp(
+            )
+            self.fusion_config.POST_MLP_FUSION = self.fusion_config.PRE_MLP_FUSION
+
         else:
             self.feed_forward = Llama4MoE(
                 num_experts=config.num_local_experts,
@@ -437,9 +438,9 @@ def __init__(
                 layer_idx=layer_idx)
 
             self.fusion_config.PRE_MOE_FUSION = model_config.mapping.has_tp(
-            ) and not self.enable_attention_dp and self.enable_fusion
-            self.fusion_config.POST_MOE_FUSION = model_config.mapping.has_tp(
-            ) and not self.enable_attention_dp and self.enable_fusion
+            ) and not self.enable_attention_dp and self.enable_fusion and not model_config.mapping.has_pp(
+            )
+            self.fusion_config.POST_MOE_FUSION = self.fusion_config.PRE_MOE_FUSION
 
         self.input_layernorm = RMSNorm(hidden_size=config.hidden_size,
                                        eps=config.rms_norm_eps,
diff --git a/tests/integration/defs/accuracy/test_llm_api_pytorch.py b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
index 481b63de168..588724b3c93 100644
--- a/tests/integration/defs/accuracy/test_llm_api_pytorch.py
+++ b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
@@ -696,8 +696,8 @@ def test_chunked_prefill(self, attn_backend):
     @parametrize_with_ids("cuda_graph", [False, True])
     @pytest.mark.parametrize(
         "tp_size,pp_size,ep_size", [(8, 1, 1), (8, 1, 4), (8, 1, 8), (4, 1, 1),
-                                    (4, 1, 2), (4, 1, 4)],
-        ids=["tp8", "tp8ep4", "tp8ep8", "tp4", "tp4ep2", "tp4ep4"])
+                                    (4, 1, 2), (4, 1, 4), (4, 2, 1)],
+        ids=["tp8", "tp8ep4", "tp8ep8", "tp4", "tp4ep2", "tp4ep4", "tp4pp2"])
     def test_fp8(self, cuda_graph, tp_size, pp_size, ep_size):
         if get_device_memory() < 140000 and get_device_count() < 8:
             pytest.skip("Not enough memory for this test")