diff --git a/python/python/lancedb/rerankers/linear_combination.py b/python/python/lancedb/rerankers/linear_combination.py
index 74f23ea61..682aac9e2 100644
--- a/python/python/lancedb/rerankers/linear_combination.py
+++ b/python/python/lancedb/rerankers/linear_combination.py
@@ -3,7 +3,6 @@
 
 
 from collections import defaultdict
-from numpy import nan
 import pyarrow as pa
 
 from .base import Reranker
@@ -66,7 +65,7 @@ class LinearCombinationReranker(Reranker):
             elif self.score == "all":
                 results = results.append_column(
                     "_distance",
-                    pa.array([nan] * len(fts_results), type=pa.float32()),
+                    pa.nulls(len(fts_results), type=pa.float32()),
                 )
             return results
 
@@ -87,7 +86,7 @@ class LinearCombinationReranker(Reranker):
             elif self.score == "all":
                 results = results.append_column(
                     "_score",
-                    pa.array([nan] * len(vector_results), type=pa.float32()),
+                    pa.nulls(len(vector_results), type=pa.float32()),
                 )
             return results
         results = defaultdict()
diff --git a/python/python/tests/test_rerankers.py b/python/python/tests/test_rerankers.py
index ac98efbfd..610f533f5 100644
--- a/python/python/tests/test_rerankers.py
+++ b/python/python/tests/test_rerankers.py
@@ -1150,6 +1150,52 @@ def test_linear_combination_missing_fts_is_penalised():
     )
 
 
+@pytest.mark.parametrize("empty_side", ["vector", "fts"])
+def test_linear_combination_empty_side_scores_are_null(empty_side):
+    """With return_score="all", the missing side's score column is null, not NaN."""
+    from lancedb.query import LanceHybridQueryBuilder
+
+    vector_results = pa.table(
+        {
+            "_rowid": pa.array([1, 2], pa.uint64()),
+            "_distance": pa.array([0.1, 0.2], pa.float32()),
+        }
+    )
+    fts_results = pa.table(
+        {
+            "_rowid": pa.array([1, 2], pa.uint64()),
+            "_score": pa.array([5.0, 4.0], pa.float32()),
+        }
+    )
+    if empty_side == "vector":
+        expected_present = fts_results["_score"].to_pylist()
+        vector_results = vector_results.slice(0, 0)
+        missing = "_distance"
+        present = "_score"
+    else:
+        expected_present = vector_results["_distance"].to_pylist()
+        fts_results = fts_results.slice(0, 0)
+        missing = "_score"
+        present = "_distance"
+
+    result = LanceHybridQueryBuilder._combine_hybrid_results(
+        fts_results=fts_results,
+        vector_results=vector_results,
+        norm="score",
+        fts_query="query",
+        reranker=LinearCombinationReranker(return_score="all"),
+        limit=10,
+        with_row_ids=True,
+    )
+
+    assert result[missing].type == pa.float32()
+    assert result[missing].null_count == len(result) == 2
+    assert result[present].to_pylist() == expected_present
+    assert result["_relevance_score"].to_pylist() == sorted(
+        result["_relevance_score"].to_pylist(), reverse=True
+    )
+
+
 @pytest.mark.skipif(
     os.environ.get("WATSONX_API_KEY") is None
     or (