diff --git a/python/python/lancedb/rerankers/rrf.py b/python/python/lancedb/rerankers/rrf.py
index 6d5b9a2ba..9c835a3ea 100644
--- a/python/python/lancedb/rerankers/rrf.py
+++ b/python/python/lancedb/rerankers/rrf.py
@@ -107,8 +107,24 @@ class RRFReranker(Reranker):
                     `search().with_row_id(True)`"
             )
 
-        combined = pa.concat_tables(vector_results, **self._concat_tables_args)
-        empty_table = pa.Table.from_arrays([], names=[])
-        reranked = self.rerank_hybrid(query, combined, empty_table)
+        # RRF ranks each result list on its own, so a document's rank is its
+        # position within the list it came from, not within the concatenation.
+        rrf_score_map = defaultdict(float)
+        for result in vector_results:
+            for i, result_id in enumerate(result["_rowid"].to_pylist(), 1):
+                rrf_score_map[result_id] += 1 / (i + self.K)
 
-        return reranked
+        combined = pa.concat_tables(vector_results, **self._concat_tables_args)
+        combined = self._deduplicate(combined)
+        relevance_scores = [
+            rrf_score_map[row_id] for row_id in combined["_rowid"].to_pylist()
+        ]
+        combined = combined.append_column(
+            "_relevance_score", pa.array(relevance_scores, type=pa.float32())
+        )
+        combined = combined.sort_by([("_relevance_score", "descending")])
+
+        if self.score == "relevance":
+            combined = self._keep_relevance_score(combined)
+
+        return combined
diff --git a/python/python/tests/test_rerankers.py b/python/python/tests/test_rerankers.py
index b4b9bc9e2..850b477a0 100644
--- a/python/python/tests/test_rerankers.py
+++ b/python/python/tests/test_rerankers.py
@@ -395,6 +395,38 @@ def test_mrr_multivector_rewards_consensus():
     assert result["_rowid"].to_pylist()[0] == 2
 
 
+def test_rrf_multivector_ranks_each_result_list():
+    # RRF scores a document by its rank *within each* result list. The top hit
+    # of the second list must score the same as the top hit of the first list,
+    # not as if it were ranked after every row of the first list.
+    reranker = RRFReranker(K=60)
+
+    def ranking(row_ids):
+        return pa.table({"_rowid": pa.array(row_ids, type=pa.int64())})
+
+    rs1 = ranking([1, 2, 3])
+    rs2 = ranking([4, 5, 6])
+
+    result = reranker.rerank_multivector([rs1, rs2])
+    scores = dict(
+        zip(result["_rowid"].to_pylist(), result["_relevance_score"].to_pylist())
+    )
+
+    assert scores[1] == pytest.approx(1 / 61)
+    assert scores[4] == pytest.approx(1 / 61)
+    assert scores[5] == pytest.approx(1 / 62)
+    # the second-ranked hit of the second list beats the third hit of the first
+    assert scores[5] > scores[3]
+
+    # A document found by both lists sums its reciprocal ranks from each list.
+    result = reranker.rerank_multivector([ranking([1, 2]), ranking([2, 3])])
+    scores = dict(
+        zip(result["_rowid"].to_pylist(), result["_relevance_score"].to_pylist())
+    )
+    assert scores[2] == pytest.approx(1 / 62 + 1 / 61)
+    assert result["_rowid"].to_pylist() == [2, 1, 3]
+
+
 def test_rrf_reranker_distance():
     data = pa.table(
         {