diff --git a/python/python/lancedb/rerankers/answerdotai.py b/python/python/lancedb/rerankers/answerdotai.py
index 0b44569e3..0e2d9c6cb 100644
--- a/python/python/lancedb/rerankers/answerdotai.py
+++ b/python/python/lancedb/rerankers/answerdotai.py
@@ -23,7 +23,7 @@ class AnswerdotaiRerankers(Reranker):
     column : str, default "text"
         The name of the column to use as input to the cross encoder model.
     return_score : str, default "relevance"
-        options are "relevance" or "all". Only "relevance" is supported for now.
+        options are "relevance" or "all".
     **kwargs
         Additional keyword arguments to pass to the model. For example, 'device'.
         See AnswerDotAI/rerankers for more information.
@@ -77,12 +77,13 @@ class AnswerdotaiRerankers(Reranker):
         vector_results: pa.Table,
         fts_results: pa.Table,
     ):
-        combined_results = self.merge_results(vector_results, fts_results)
+        if self.score == "all":
+            combined_results = self._merge_and_keep_scores(vector_results, fts_results)
+        else:
+            combined_results = self.merge_results(vector_results, fts_results)
         combined_results = self._rerank(combined_results, query)
         if self.score == "relevance":
             combined_results = self._keep_relevance_score(combined_results)
-        elif self.score == "all":
-            combined_results = self._merge_and_keep_scores(vector_results, fts_results)
         combined_results = combined_results.sort_by(
             [("_relevance_score", "descending")]
         )
diff --git a/python/python/lancedb/rerankers/colbert.py b/python/python/lancedb/rerankers/colbert.py
index a7a98b361..ff3bc8c4a 100644
--- a/python/python/lancedb/rerankers/colbert.py
+++ b/python/python/lancedb/rerankers/colbert.py
@@ -16,7 +16,7 @@ class ColbertReranker(AnswerdotaiRerankers):
     column : str, default "text"
         The name of the column to use as input to the cross encoder model.
     return_score : str, default "relevance"
-        options are "relevance" or "all". Only "relevance" is supported for now.
+        options are "relevance" or "all".
     **kwargs
         Additional keyword arguments to pass to the model, for example, 'device'.
         See AnswerDotAI/rerankers for more information.
diff --git a/python/python/tests/test_rerankers.py b/python/python/tests/test_rerankers.py
index 7c2b52ffb..372a6b0f7 100644
--- a/python/python/tests/test_rerankers.py
+++ b/python/python/tests/test_rerankers.py
@@ -644,6 +644,21 @@ def test_cross_encoder_reranker_return_all(tmp_path):
     assert "_distance" in result.column_names
 
 
+def test_answerdotai_reranker_return_all(tmp_path):
+    pytest.importorskip("rerankers")
+    reranker = AnswerdotaiRerankers(return_score="all")
+    table, schema = get_test_table(tmp_path)
+    query = "single player experience"
+    result = (
+        table.search(query, query_type="hybrid", vector_column_name="vector")
+        .rerank(reranker=reranker)
+        .to_arrow()
+    )
+    assert "_relevance_score" in result.column_names
+    assert "_score" in result.column_names
+    assert "_distance" in result.column_names
+
+
 # ---------------------------------------------------------------------------
 # Regression tests for LinearCombinationReranker scoring bugs (issue #3154)
 # ---------------------------------------------------------------------------