diff --git a/bigframes/core/compile/sqlglot/expressions/numeric_ops.py b/bigframes/core/compile/sqlglot/expressions/numeric_ops.py
index e33702b08c..e0ea24a470 100644
--- a/bigframes/core/compile/sqlglot/expressions/numeric_ops.py
+++ b/bigframes/core/compile/sqlglot/expressions/numeric_ops.py
@@ -350,6 +350,13 @@ def _(left: TypedExpr, right: TypedExpr) -> sge.Expression:
     return result
 
 
+@register_binary_op(ops.manhattan_distance_op)
+def _(left: TypedExpr, right: TypedExpr) -> sge.Expression:
+    return sge.func(
+        "ML.DISTANCE", left.expr, right.expr, sge.Literal.string("MANHATTAN")
+    )
+
+
 @register_binary_op(ops.mod_op)
 def _(left: TypedExpr, right: TypedExpr) -> sge.Expression:
     # In BigQuery returned value has the same sign as X. In pandas, the sign of y is used, so we need to flip the result if sign(x) != sign(y)
diff --git a/tests/unit/core/compile/sqlglot/expressions/snapshots/test_numeric_ops/test_manhattan_distance/out.sql b/tests/unit/core/compile/sqlglot/expressions/snapshots/test_numeric_ops/test_manhattan_distance/out.sql
new file mode 100644
index 0000000000..185bb7b277
--- /dev/null
+++ b/tests/unit/core/compile/sqlglot/expressions/snapshots/test_numeric_ops/test_manhattan_distance/out.sql
@@ -0,0 +1,16 @@
+WITH `bfcte_0` AS (
+  SELECT
+    `float_list_col`,
+    `numeric_list_col`
+  FROM `bigframes-dev`.`sqlglot_test`.`repeated_types`
+), `bfcte_1` AS (
+  SELECT
+    *,
+    ML.DISTANCE(`float_list_col`, `float_list_col`, 'MANHATTAN') AS `bfcol_2`,
+    ML.DISTANCE(`numeric_list_col`, `numeric_list_col`, 'MANHATTAN') AS `bfcol_3`
+  FROM `bfcte_0`
+)
+SELECT
+  `bfcol_2` AS `float_list_col`,
+  `bfcol_3` AS `numeric_list_col`
+FROM `bfcte_1`
\ No newline at end of file
diff --git a/tests/unit/core/compile/sqlglot/expressions/test_numeric_ops.py b/tests/unit/core/compile/sqlglot/expressions/test_numeric_ops.py
index c58ce9e2f1..5d3b23ebb7 100644
--- a/tests/unit/core/compile/sqlglot/expressions/test_numeric_ops.py
+++ b/tests/unit/core/compile/sqlglot/expressions/test_numeric_ops.py
@@ -354,6 +354,21 @@ def test_floordiv_timedelta(scalar_types_df: bpd.DataFrame, snapshot):
     snapshot.assert_match(bf_df.sql, "out.sql")
 
 
+def test_manhattan_distance(repeated_types_df: bpd.DataFrame, snapshot):
+    col_names = ["float_list_col", "numeric_list_col"]
+    bf_df = repeated_types_df[col_names]
+
+    sql = utils._apply_ops_to_sql(
+        bf_df,
+        [
+            ops.manhattan_distance_op.as_expr("float_list_col", "float_list_col"),
+            ops.manhattan_distance_op.as_expr("numeric_list_col", "numeric_list_col"),
+        ],
+        ["float_list_col", "numeric_list_col"],
+    )
+    snapshot.assert_match(sql, "out.sql")
+
+
 def test_mul_numeric(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["int64_col", "bool_col"]]