diff --git a/megatron/core/fusions/fused_mla_yarn_rope_apply.py b/megatron/core/fusions/fused_mla_yarn_rope_apply.py
index 1fd5dcfae37..f75183d7490 100644
--- a/megatron/core/fusions/fused_mla_yarn_rope_apply.py
+++ b/megatron/core/fusions/fused_mla_yarn_rope_apply.py
@@ -253,6 +253,12 @@ def forward(
         assert sin.is_contiguous()
         assert headdim == qk_head_dim + emb_dim
         assert emb_dim % 4 == 0
+        if cos.shape[-1] != emb_dim or sin.shape[-1] != emb_dim:
+            raise ValueError(
+                f"cos/sin last dim must equal emb_dim={emb_dim} "
+                f"(got cos={cos.shape[-1]}, sin={sin.shape[-1]}); a narrower rotary cache "
+                f"(e.g. rotary_percent < 1) makes the fused MLA kernel read past the buffer."
+            )
 
         grid = lambda META: (total_seqlen, triton.cdiv(nheads, META["BLOCK_H"]))
         rotary_fwd_q_kernel[grid](
@@ -629,6 +635,12 @@ def forward(
         assert cos.is_contiguous()
         assert sin.is_contiguous()
         assert emb_dim % 4 == 0
+        if cos.shape[-1] != emb_dim or sin.shape[-1] != emb_dim:
+            raise ValueError(
+                f"cos/sin last dim must equal emb_dim={emb_dim} "
+                f"(got cos={cos.shape[-1]}, sin={sin.shape[-1]}); a narrower rotary cache "
+                f"(e.g. rotary_percent < 1) makes the fused MLA kernel read past the buffer."
+            )
 
         o_key = kv.new_empty(total_seqlen, nheads, emb_dim + k_dim)
         o_value = kv.new_empty(total_seqlen, nheads, v_dim)
diff --git a/tests/unit_tests/fusions/test_mla_yarn_rope_apply.py b/tests/unit_tests/fusions/test_mla_yarn_rope_apply.py
index 810f48092ee..169d004cf73 100644
--- a/tests/unit_tests/fusions/test_mla_yarn_rope_apply.py
+++ b/tests/unit_tests/fusions/test_mla_yarn_rope_apply.py
@@ -364,3 +364,51 @@ def test_mla_rotary_interleaved_with_apply_rope_fusion_emits_warning_and_uses_un
             call_kw = unfused_spy.call_args[1]
             assert call_kw["mla_rotary_interleaved"] is True
         assert out.shape == t.shape
+
+
+class TestFusedApplyMLARopeCosWidthGuard:
+    """The fused MLA RoPE kernels read ``emb_dim`` cos/sin values per token and assume the
+    cache is ``emb_dim`` wide. A narrower cache (e.g. ``rotary_percent < 1`` shrinks it to
+    ``int(emb_dim * rotary_percent)``) makes the kernel read past the buffer and return
+    garbage. These tests assert the guard rejects that up front, before the kernel launches,
+    so they do not require CUDA."""
+
+    @pytest.mark.skipif(
+        fused_apply_mla_rope_for_q is None, reason="fused MLA RoPE kernels unavailable"
+    )
+    def test_q_rejects_narrow_cos_sin(self):
+        qk_head_dim = 128
+        emb_dim = 64
+        num_heads = 4
+        seqlen = 8
+        batch_size = 2
+        narrow = emb_dim // 8  # mimics rotary_percent=0.125 -> int(64 * 0.125) = 8
+
+        q = torch.randn(seqlen, batch_size, num_heads, qk_head_dim + emb_dim)
+        cos = torch.randn(seqlen, 1, 1, narrow)
+        sin = torch.randn(seqlen, 1, 1, narrow)
+
+        with pytest.raises(ValueError, match="cos/sin last dim"):
+            fused_apply_mla_rope_for_q(q, cos, sin, qk_head_dim, emb_dim, cu_seqlens_q=None)
+
+    @pytest.mark.skipif(
+        fused_apply_mla_rope_for_kv is None, reason="fused MLA RoPE kernels unavailable"
+    )
+    def test_kv_rejects_narrow_cos_sin(self):
+        emb_dim = 64
+        k_dim = 128
+        v_dim = 128
+        num_heads = 4
+        seqlen = 8
+        batch_size = 2
+        narrow = emb_dim // 8
+
+        kv = torch.randn(seqlen, batch_size, num_heads, k_dim + v_dim)
+        k_pos_emb = torch.randn(seqlen, batch_size, 1, emb_dim)
+        cos = torch.randn(seqlen, 1, 1, narrow)
+        sin = torch.randn(seqlen, 1, 1, narrow)
+
+        with pytest.raises(ValueError, match="cos/sin last dim"):
+            fused_apply_mla_rope_for_kv(
+                kv, k_pos_emb, cos, sin, emb_dim, k_dim, v_dim, cu_seqlens_kv=None
+            )