diff --git a/vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py b/vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py
index 8090ef19cb0..7c2230e82aa 100644
--- a/vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py
+++ b/vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py
@@ -25,6 +25,8 @@
 from vllm.config.compilation import Range
 from vllm.logger import logger
 
+from vllm_ascend.ops.rotary_embedding import get_rope_dim
+
 
 class QKNormRopeFusionPattern:
 
@@ -252,12 +254,16 @@ def __init__(self, vllm_config: VllmConfig):
             )
             return
         layer = next(iter(attn_layers.values()))
+        rope_dim = get_rope_dim(vllm_config)
+        if layer.head_size != 128 or rope_dim != layer.head_size:
+            logger.debug(
+                f"Currently, QKNorm and Rope fusion is only supported where"
+                f"rotary_dim == head_size and head_size == 128. But rotary_dim"
+                f"is {rope_dim} and head_size is {layer.head_size}. Therefore"
+                f"the fusion is skipped.")
+            return
+
         for epsilon in [1e-6, 1e-5]:
-            if layer.head_size != 128:
-                logger.debug(
-                    "QKNorm and Rope fusion not enabled: head_dim %d is not equal of 128",
-                    layer.head_size)
-                continue
             QKNormRopeFusionPattern(vllm_config=vllm_config,
                                     head_dim=layer.head_size,
                                     num_heads=layer.num_heads,
diff --git a/vllm_ascend/ops/rotary_embedding.py b/vllm_ascend/ops/rotary_embedding.py
index 79bfa0a2549..b9b94e12b8d 100644
--- a/vllm_ascend/ops/rotary_embedding.py
+++ b/vllm_ascend/ops/rotary_embedding.py
@@ -36,6 +36,24 @@
 
     from vllm_ascend.ops.triton.rope import rope_forward_triton
 
+
+def get_rope_dim(vllm_config):
+    model_config = vllm_config.model_config
+
+    if model_config.use_mla:
+        rope_dim = model_config.hf_text_config.qk_rope_head_dim
+    else:
+        rope_dim = model_config.get_head_size()
+        # For models using partial rope like Qwen3-Next.
+        if hasattr(model_config.hf_text_config, "partial_rotary_factor"):
+            rope_dim = int(rope_dim *
+                           model_config.hf_text_config.partial_rotary_factor)
+        elif hasattr(model_config.hf_text_config, "rotary_dim"):
+            rope_dim = int(model_config.hf_text_config.rotary_dim)
+
+    return rope_dim
+
+
 # Currently, rope ops used on npu requires detached cos && sin as inputs.
 # However, RotaryEmbedding in vllm use cos_sin_cache as a whole variable.
 # So we have to preprocess cos_sin_cache int cos && sin. In the future,
@@ -73,7 +91,7 @@ def set_cos_and_sin(vllm_config, max_num_reqs, decode_token_per_req, dtype,
     max_num_batched_tokens = vllm_config.scheduler_config.max_num_batched_tokens
 
     if model_config.use_mla:
-        rope_dim = model_config.hf_text_config.qk_rope_head_dim
+        rope_dim = get_rope_dim(vllm_config)
         _cos_mla = torch.ones(max_num_batched_tokens,
                               1,
                               1,
@@ -87,11 +105,7 @@ def set_cos_and_sin(vllm_config, max_num_reqs, decode_token_per_req, dtype,
                                dtype=dtype,
                                device=device)
     elif not is_vl_model(vllm_config) and has_rope(vllm_config):
-        rope_dim = model_config.get_head_size()
-        # For models using partial rope like Qwen3-Next.
-        if hasattr(model_config.hf_text_config, "partial_rotary_factor"):
-            rope_dim = int(rope_dim *
-                           model_config.hf_text_config.partial_rotary_factor)
+        rope_dim = get_rope_dim(vllm_config)
         _cos = torch.ones(1,
                           max_num_batched_tokens,
                           1,