diff --git a/megatron/core/extensions/transformer_engine.py b/megatron/core/extensions/transformer_engine.py
index 20f0ece635e..f82dabcb618 100644
--- a/megatron/core/extensions/transformer_engine.py
+++ b/megatron/core/extensions/transformer_engine.py
@@ -2385,6 +2385,7 @@ def fused_apply_rotary_pos_emb_thd(
         freqs: torch.Tensor,
         cp_size: int = 1,
         cp_rank: int = 0,
+        interleaved: bool = False,
     ) -> torch.Tensor:
         """
         Apply rotary positional embedding to input tensor T in `thd` format with CP support.
@@ -2398,6 +2399,7 @@ def fused_apply_rotary_pos_emb_thd(
                 cu_seqlens=cu_seqlens,
                 cp_size=cp_size,
                 cp_rank=cp_rank,
+                interleaved=interleaved,
             )
         else:
             assert cp_size == 1, "Only TE >= 1.12 supports RoPE fusion for THD format with CP."
diff --git a/megatron/core/models/common/embeddings/rope_utils.py b/megatron/core/models/common/embeddings/rope_utils.py
index 0e00c6340ed..b990615da29 100644
--- a/megatron/core/models/common/embeddings/rope_utils.py
+++ b/megatron/core/models/common/embeddings/rope_utils.py
@@ -313,7 +313,12 @@ def apply_rotary_pos_emb(
         else:
             assert fused_apply_rotary_pos_emb_thd is not None, "apply_rope_fusion is not available."
             return fused_apply_rotary_pos_emb_thd(
-                t, cu_seqlens, freqs, cp_size=cp_group.size(), cp_rank=cp_group.rank()
+                t,
+                cu_seqlens,
+                freqs,
+                cp_size=cp_group.size(),
+                cp_rank=cp_group.rank(),
+                interleaved=config.rotary_interleaved,
             )
     # use unfused implementation
     if cu_seqlens is None: