diff --git a/python/python/lancedb/query.py b/python/python/lancedb/query.py
index 751135209..926b51527 100644
--- a/python/python/lancedb/query.py
+++ b/python/python/lancedb/query.py
@@ -2118,19 +2118,17 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
         """  # noqa: E501
         self._create_query_builders()
 
-        results = ["Vector Search Plan:"]
-        results.append(
-            self._table._explain_plan(
-                self._vector_query.to_query_object(), verbose=verbose
-            )
+        reranker_label = str(self._reranker) if self._reranker else "No reranker"
+        vector_plan = self._table._explain_plan(
+            self._vector_query.to_query_object(), verbose=verbose
         )
-        results.append("FTS Search Plan:")
-        results.append(
-            self._table._explain_plan(
-                self._fts_query.to_query_object(), verbose=verbose
-            )
+        fts_plan = self._table._explain_plan(
+            self._fts_query.to_query_object(), verbose=verbose
         )
-        return "\n".join(results)
+        # Indent sub-plans under the reranker
+        indented_vector = "\n".join("  " + line for line in vector_plan.splitlines())
+        indented_fts = "\n".join("  " + line for line in fts_plan.splitlines())
+        return f"{reranker_label}\n  {indented_vector}\n  {indented_fts}"
 
     def analyze_plan(self):
         """Execute the query and display with runtime metrics.
@@ -3164,23 +3162,20 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         ...     plan = await table.query().nearest_to([1.0, 2.0]).nearest_to_text("hello").explain_plan(True)
         ...     print(plan)
         >>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
-        Vector Search Plan:
-        ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
-          Take: columns="vector, _rowid, _distance, (text)"
-            CoalesceBatchesExec: target_batch_size=1024
-              GlobalLimitExec: skip=0, fetch=10
-                FilterExec: _distance@2 IS NOT NULL
-                  SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
-                    KNNVectorDistance: metric=l2
-                      LanceRead: uri=..., projection=[vector], ...
-        <BLANKLINE>
-        FTS Search Plan:
-        ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
-          Take: columns="_rowid, _score, (vector), (text)"
-            CoalesceBatchesExec: target_batch_size=1024
-              GlobalLimitExec: skip=0, fetch=10
-                MatchQuery: column=text, query=hello
-        <BLANKLINE>
+        RRFReranker(K=60)
+            ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
+              Take: columns="vector, _rowid, _distance, (text)"
+                CoalesceBatchesExec: target_batch_size=1024
+                  GlobalLimitExec: skip=0, fetch=10
+                    FilterExec: _distance@2 IS NOT NULL
+                      SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
+                        KNNVectorDistance: metric=l2
+                          LanceRead: uri=..., projection=[vector], ...
+            ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
+              Take: columns="_rowid, _score, (vector), (text)"
+                CoalesceBatchesExec: target_batch_size=1024
+                  GlobalLimitExec: skip=0, fetch=10
+                    MatchQuery: column=text, query=hello
 
         Parameters
         ----------
@@ -3192,12 +3187,12 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         plan : str
         """  # noqa: E501
 
-        results = ["Vector Search Plan:"]
-        results.append(await self._inner.to_vector_query().explain_plan(verbose))
-        results.append("FTS Search Plan:")
-        results.append(await self._inner.to_fts_query().explain_plan(verbose))
-
-        return "\n".join(results)
+        vector_plan = await self._inner.to_vector_query().explain_plan(verbose)
+        fts_plan = await self._inner.to_fts_query().explain_plan(verbose)
+        # Indent sub-plans under the reranker
+        indented_vector = "\n".join("  " + line for line in vector_plan.splitlines())
+        indented_fts = "\n".join("  " + line for line in fts_plan.splitlines())
+        return f"{self._reranker}\n  {indented_vector}\n  {indented_fts}"
 
     async def analyze_plan(self):
         """
diff --git a/python/python/lancedb/rerankers/answerdotai.py b/python/python/lancedb/rerankers/answerdotai.py
index d615ed317..0b44569e3 100644
--- a/python/python/lancedb/rerankers/answerdotai.py
+++ b/python/python/lancedb/rerankers/answerdotai.py
@@ -42,10 +42,18 @@ class AnswerdotaiRerankers(Reranker):
         rerankers = attempt_import_or_raise(
             "rerankers"
         )  # import here for faster ops later
+        self.model_name = model_name
+        self.model_type = model_type
         self.reranker = rerankers.Reranker(
             model_name=model_name, model_type=model_type, **kwargs
         )
 
+    def __str__(self):
+        return (
+            f"AnswerdotaiRerankers(model_type={self.model_type}, "
+            f"model_name={self.model_name})"
+        )
+
     def _rerank(self, result_set: pa.Table, query: str):
         result_set = self._handle_empty_results(result_set)
         if len(result_set) == 0:
diff --git a/python/python/lancedb/rerankers/base.py b/python/python/lancedb/rerankers/base.py
index 0c546a772..7bc7ff105 100644
--- a/python/python/lancedb/rerankers/base.py
+++ b/python/python/lancedb/rerankers/base.py
@@ -40,6 +40,9 @@ class Reranker(ABC):
         if ARROW_VERSION.major <= 13:
             self._concat_tables_args = {"promote": True}
 
+    def __str__(self):
+        return self.__class__.__name__
+
     def rerank_vector(
         self,
         query: str,
diff --git a/python/python/lancedb/rerankers/cohere.py b/python/python/lancedb/rerankers/cohere.py
index 107960671..efd752c22 100644
--- a/python/python/lancedb/rerankers/cohere.py
+++ b/python/python/lancedb/rerankers/cohere.py
@@ -44,6 +44,9 @@ class CohereReranker(Reranker):
         self.top_n = top_n
         self.api_key = api_key
 
+    def __str__(self):
+        return f"CohereReranker(model_name={self.model_name})"
+
     @cached_property
     def _client(self):
         cohere = attempt_import_or_raise("cohere")
diff --git a/python/python/lancedb/rerankers/cross_encoder.py b/python/python/lancedb/rerankers/cross_encoder.py
index fd24eed11..30ad9d382 100644
--- a/python/python/lancedb/rerankers/cross_encoder.py
+++ b/python/python/lancedb/rerankers/cross_encoder.py
@@ -50,6 +50,9 @@ class CrossEncoderReranker(Reranker):
         if self.device is None:
             self.device = "cuda" if torch.cuda.is_available() else "cpu"
 
+    def __str__(self):
+        return f"CrossEncoderReranker(model_name={self.model_name})"
+
     @cached_property
     def model(self):
         sbert = attempt_import_or_raise("sentence_transformers")
diff --git a/python/python/lancedb/rerankers/jinaai.py b/python/python/lancedb/rerankers/jinaai.py
index 84ab21f4f..349a8eca5 100644
--- a/python/python/lancedb/rerankers/jinaai.py
+++ b/python/python/lancedb/rerankers/jinaai.py
@@ -45,6 +45,9 @@ class JinaReranker(Reranker):
         self.top_n = top_n
         self.api_key = api_key
 
+    def __str__(self):
+        return f"JinaReranker(model_name={self.model_name})"
+
     @cached_property
     def _client(self):
         import requests
diff --git a/python/python/lancedb/rerankers/linear_combination.py b/python/python/lancedb/rerankers/linear_combination.py
index a22c7b8d9..9f1d645c9 100644
--- a/python/python/lancedb/rerankers/linear_combination.py
+++ b/python/python/lancedb/rerankers/linear_combination.py
@@ -38,6 +38,9 @@ class LinearCombinationReranker(Reranker):
         self.weight = weight
         self.fill = fill
 
+    def __str__(self):
+        return f"LinearCombinationReranker(weight={self.weight}, fill={self.fill})"
+
     def rerank_hybrid(
         self,
         query: str,  # noqa: F821
diff --git a/python/python/lancedb/rerankers/mrr.py b/python/python/lancedb/rerankers/mrr.py
index c4860ff23..e2d5d1a97 100644
--- a/python/python/lancedb/rerankers/mrr.py
+++ b/python/python/lancedb/rerankers/mrr.py
@@ -54,6 +54,12 @@ class MRRReranker(Reranker):
         self.weight_vector = weight_vector
         self.weight_fts = weight_fts
 
+    def __str__(self):
+        return (
+            f"MRRReranker(weight_vector={self.weight_vector}, "
+            f"weight_fts={self.weight_fts})"
+        )
+
     def rerank_hybrid(
         self,
         query: str,  # noqa: F821
diff --git a/python/python/lancedb/rerankers/openai.py b/python/python/lancedb/rerankers/openai.py
index 7b181e806..4cbbb0822 100644
--- a/python/python/lancedb/rerankers/openai.py
+++ b/python/python/lancedb/rerankers/openai.py
@@ -43,6 +43,9 @@ class OpenaiReranker(Reranker):
         self.column = column
         self.api_key = api_key
 
+    def __str__(self):
+        return f"OpenaiReranker(model_name={self.model_name})"
+
     def _rerank(self, result_set: pa.Table, query: str):
         result_set = self._handle_empty_results(result_set)
         if len(result_set) == 0:
diff --git a/python/python/lancedb/rerankers/rrf.py b/python/python/lancedb/rerankers/rrf.py
index cbb38caee..f512d7a8c 100644
--- a/python/python/lancedb/rerankers/rrf.py
+++ b/python/python/lancedb/rerankers/rrf.py
@@ -36,6 +36,9 @@ class RRFReranker(Reranker):
         super().__init__(return_score)
         self.K = K
 
+    def __str__(self):
+        return f"RRFReranker(K={self.K})"
+
     def rerank_hybrid(
         self,
         query: str,  # noqa: F821
diff --git a/python/python/lancedb/rerankers/voyageai.py b/python/python/lancedb/rerankers/voyageai.py
index 47fb45c04..0f41ba927 100644
--- a/python/python/lancedb/rerankers/voyageai.py
+++ b/python/python/lancedb/rerankers/voyageai.py
@@ -52,6 +52,9 @@ class VoyageAIReranker(Reranker):
         self.api_key = api_key
         self.truncation = truncation
 
+    def __str__(self):
+        return f"VoyageAIReranker(model_name={self.model_name})"
+
     @cached_property
     def _client(self):
         voyageai = attempt_import_or_raise("voyageai")
diff --git a/python/python/tests/test_hybrid_query.py b/python/python/tests/test_hybrid_query.py
index 3957568a5..bb6f2befc 100644
--- a/python/python/tests/test_hybrid_query.py
+++ b/python/python/tests/test_hybrid_query.py
@@ -163,9 +163,7 @@ async def test_explain_plan(table: AsyncTable):
         table.query().nearest_to_text("dog").nearest_to([0.1, 0.1]).explain_plan(True)
     )
 
-    assert "Vector Search Plan" in plan
     assert "KNNVectorDistance" in plan
-    assert "FTS Search Plan" in plan
     assert "LanceRead" in plan