diff --git a/src/diffusers/models/transformers/transformer_qwenimage.py b/src/diffusers/models/transformers/transformer_qwenimage.py
index c5419b9f107e..d88aef4dcf2a 100644
--- a/src/diffusers/models/transformers/transformer_qwenimage.py
+++ b/src/diffusers/models/transformers/transformer_qwenimage.py
@@ -933,6 +933,7 @@ def forward(
             batch_size, image_seq_len = hidden_states.shape[:2]
             image_mask = torch.ones((batch_size, image_seq_len), dtype=torch.bool, device=hidden_states.device)
             joint_attention_mask = torch.cat([encoder_hidden_states_mask, image_mask], dim=1)
+            joint_attention_mask = joint_attention_mask[:, None, None, :]
             block_attention_kwargs["attention_mask"] = joint_attention_mask
 
         for index_block, block in enumerate(self.transformer_blocks):
diff --git a/tests/models/testing_utils/parallelism.py b/tests/models/testing_utils/parallelism.py
index 2b6aab59a662..bea832904041 100644
--- a/tests/models/testing_utils/parallelism.py
+++ b/tests/models/testing_utils/parallelism.py
@@ -200,7 +200,6 @@ def test_context_parallel_inference(self, cp_type, batch_size: int = 1):
             f"Context parallel inference failed: {return_dict.get('error', 'Unknown error')}"
         )
 
-    @pytest.mark.xfail(reason="Context parallel may not support batch_size > 1")
     @pytest.mark.parametrize("cp_type", ["ulysses_degree", "ring_degree"], ids=["ulysses", "ring"])
     def test_context_parallel_batch_inputs(self, cp_type):
         self.test_context_parallel_inference(cp_type, batch_size=2)