diff --git a/rust/lance-index/src/scalar/inverted/index.rs b/rust/lance-index/src/scalar/inverted/index.rs
index 3605364715e..74ecc3c78b6 100644
--- a/rust/lance-index/src/scalar/inverted/index.rs
+++ b/rust/lance-index/src/scalar/inverted/index.rs
@@ -302,11 +302,23 @@ impl InvertedIndex {
             .collect::<Vec<_>>();
         let mut parts = stream::iter(parts).buffer_unordered(get_num_compute_intensive_cpus());
         let scorer = IndexBM25Scorer::new(self.partitions.iter().map(|part| part.as_ref()));
+        let mut idf_cache: HashMap<String, f32> = HashMap::new();
         while let Some(res) = parts.try_next().await? {
             if res.candidates.is_empty() {
                 continue;
             }
-            let tokens_by_position = &res.tokens_by_position;
+            let mut idf_by_position = Vec::with_capacity(res.tokens_by_position.len());
+            for token in &res.tokens_by_position {
+                let idf_weight = match idf_cache.get(token) {
+                    Some(weight) => *weight,
+                    None => {
+                        let weight = scorer.query_weight(token);
+                        idf_cache.insert(token.clone(), weight);
+                        weight
+                    }
+                };
+                idf_by_position.push(idf_weight);
+            }
             for DocCandidate {
                 row_id,
                 freqs,
@@ -315,9 +327,9 @@ impl InvertedIndex {
             {
                 let mut score = 0.0;
                 for (term_index, freq) in freqs.into_iter() {
-                    debug_assert!((term_index as usize) < tokens_by_position.len());
-                    let token = &tokens_by_position[term_index as usize];
-                    score += scorer.score(token.as_str(), freq, doc_length);
+                    debug_assert!((term_index as usize) < idf_by_position.len());
+                    score +=
+                        idf_by_position[term_index as usize] * scorer.doc_weight(freq, doc_length);
                 }
                 if candidates.len() < limit {
                     candidates.push(Reverse(ScoredDoc::new(row_id, score)));
@@ -2790,4 +2802,86 @@ mod tests {
         assert_eq!(block_max_scores.len(), expected_blocks);
         assert_eq!(block_max_scores.capacity(), expected_blocks);
     }
+
+    #[tokio::test]
+    async fn test_bm25_search_uses_global_idf() {
+        let tmpdir = TempObjDir::default();
+        let store = Arc::new(LanceIndexStore::new(
+            ObjectStore::local().into(),
+            tmpdir.clone(),
+            Arc::new(LanceCache::no_cache()),
+        ));
+
+        // Partition 0: 3 docs, only one contains "alpha".
+        let mut builder0 = InnerBuilder::new(0, false, TokenSetFormat::default());
+        builder0.tokens.add("alpha".to_owned());
+        builder0.tokens.add("beta".to_owned());
+        builder0.posting_lists.push(PostingListBuilder::new(false));
+        builder0.posting_lists.push(PostingListBuilder::new(false));
+        builder0.posting_lists[0].add(0, PositionRecorder::Count(1));
+        builder0.posting_lists[1].add(1, PositionRecorder::Count(1));
+        builder0.posting_lists[1].add(2, PositionRecorder::Count(1));
+        builder0.docs.append(100, 1);
+        builder0.docs.append(101, 1);
+        builder0.docs.append(102, 1);
+        builder0.write(store.as_ref()).await.unwrap();
+
+        // Partition 1: 1 doc, contains "alpha".
+        let mut builder1 = InnerBuilder::new(1, false, TokenSetFormat::default());
+        builder1.tokens.add("alpha".to_owned());
+        builder1.posting_lists.push(PostingListBuilder::new(false));
+        builder1.posting_lists[0].add(0, PositionRecorder::Count(1));
+        builder1.docs.append(200, 1);
+        builder1.write(store.as_ref()).await.unwrap();
+
+        let metadata = std::collections::HashMap::from_iter(vec![
+            (
+                "partitions".to_owned(),
+                serde_json::to_string(&vec![0u64, 1u64]).unwrap(),
+            ),
+            (
+                "params".to_owned(),
+                serde_json::to_string(&InvertedIndexParams::default()).unwrap(),
+            ),
+            (
+                TOKEN_SET_FORMAT_KEY.to_owned(),
+                TokenSetFormat::default().to_string(),
+            ),
+        ]);
+        let mut writer = store
+            .new_index_file(METADATA_FILE, Arc::new(arrow_schema::Schema::empty()))
+            .await
+            .unwrap();
+        writer.finish_with_metadata(metadata).await.unwrap();
+
+        let cache = Arc::new(LanceCache::with_capacity(4096));
+        let index = InvertedIndex::load(store.clone(), None, cache.as_ref())
+            .await
+            .unwrap();
+
+        let tokens = Arc::new(Tokens::new(vec!["alpha".to_string()], DocType::Text));
+        let params = Arc::new(FtsSearchParams::new().with_limit(Some(10)));
+        let prefilter = Arc::new(NoFilter);
+        let metrics = Arc::new(NoOpMetricsCollector);
+
+        let (row_ids, scores) = index
+            .bm25_search(tokens, params, Operator::Or, prefilter, metrics)
+            .await
+            .unwrap();
+
+        assert_eq!(row_ids.len(), 2);
+        assert!(row_ids.contains(&100));
+        assert!(row_ids.contains(&200));
+        assert_eq!(row_ids.len(), scores.len());
+
+        let expected_idf = idf(2, 4);
+        for score in scores {
+            assert!(
+                (score - expected_idf).abs() < 1e-6,
+                "score: {}, expected: {}",
+                score,
+                expected_idf
+            );
+        }
+    }
 }