diff --git a/tests/model_executor/test_triton_dispatcher.py b/tests/model_executor/test_triton_dispatcher.py
index 909230c40f..09faa74a2d 100644
--- a/tests/model_executor/test_triton_dispatcher.py
+++ b/tests/model_executor/test_triton_dispatcher.py
@@ -220,3 +220,44 @@ def test_real_triton_kernel_override_end_to_end() -> None:
         "out_ptr",
         "BLOCK",
     )
+
+
+def test_cpu_slot_mapping_override_forwards_kernel_arguments(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    from vllm.utils import cpu_triton_utils
+    from vllm.v1.worker.block_table import ComputeSlotMappingKernel
+
+    calls: list[tuple[Any, ...]] = []
+    fake_torch = types.SimpleNamespace(
+        ops=types.SimpleNamespace(
+            _C=types.SimpleNamespace(
+                compute_slot_mapping_kernel_impl=lambda *args: calls.append(args)
+            )
+        )
+    )
+    monkeypatch.setattr(cpu_triton_utils, "torch", fake_torch)
+
+    override = KernelOverride(
+        ComputeSlotMappingKernel.kernel,
+        cpu_triton_utils._compute_slot_mapping_kernel_impl,
+    )
+    override[(2,)](
+        num_tokens=2,
+        max_num_tokens=4,
+        query_start_loc_ptr="query_start_loc",
+        positions_ptr="positions",
+        block_table_ptr="block_table",
+        block_table_stride=128,
+        slot_mapping_ptr="slot_mapping",
+        KV_CACHE_BLOCK_SIZE=16,
+        TOTAL_CP_WORLD_SIZE=1,
+        TOTAL_CP_RANK=0,
+        CP_KV_CACHE_INTERLEAVE_SIZE=1,
+        PAD_ID=-1,
+        BLOCK_SIZE=1024,
+    )
+
+    assert calls == [
+        ("query_start_loc", "positions", "block_table", "slot_mapping", 16)
+    ]
diff --git a/vllm/utils/cpu_triton_utils.py b/vllm/utils/cpu_triton_utils.py
index d8e4cd389d..3950e4c2ac 100644
--- a/vllm/utils/cpu_triton_utils.py
+++ b/vllm/utils/cpu_triton_utils.py
@@ -16,10 +16,8 @@ def _compute_slot_mapping_kernel_impl(
     positions: torch.Tensor,  # [num_tokens], int64
     block_table: torch.Tensor,  # [max_num_reqs, max_num_blocks_per_req], int32
     block_table_stride: int,  # max_num_blocks_per_req
-    block_size: int,
     slot_mapping: torch.Tensor,  # [max_num_tokens], int64
-    KV_CACHE_BLOCK_SIZE: int | None = None,
-    BLOCKS_PER_KV_BLOCK: int = 1,
+    KV_CACHE_BLOCK_SIZE: int,
     TOTAL_CP_WORLD_SIZE: int = 1,
     TOTAL_CP_RANK: int = 0,
     CP_KV_CACHE_INTERLEAVE_SIZE: int = 1,
@@ -27,14 +25,12 @@ def _compute_slot_mapping_kernel_impl(
     BLOCK_SIZE: int = 1024,
 ) -> None:
     assert TOTAL_CP_WORLD_SIZE == 1, "Context Parallelism is not supported on CPU."
-    if BLOCKS_PER_KV_BLOCK != 1:
-        assert block_size * BLOCKS_PER_KV_BLOCK == KV_CACHE_BLOCK_SIZE
     torch.ops._C.compute_slot_mapping_kernel_impl(
         query_start_loc,
         positions,
         block_table,
         slot_mapping,
-        block_size,
+        KV_CACHE_BLOCK_SIZE,
     )