diff --git a/collection.go b/collection.go
index 2a2c859..68be66f 100644
--- a/collection.go
+++ b/collection.go
@@ -347,6 +347,7 @@ func (c *Collection) Query(ctx context.Context, queryText string, nResults int,
 //
 //   - queryEmbedding: The embedding of the query to search for. It must be created
 //     with the same embedding model as the document embeddings in the collection.
+//     The embedding will be normalized if it's not the case yet.
 //   - nResults: The number of results to return. Must be > 0.
 //   - where: Conditional filtering on metadata. Optional.
 //   - whereDocument: Conditional filtering on documents. Optional.
@@ -382,6 +383,12 @@ func (c *Collection) QueryEmbedding(ctx context.Context, queryEmbedding []float3
 		return nil, nil
 	}
 
+	// Normalize embedding if not the case yet. We only support cosine similarity
+	// for now and all documents were already normalized when added to the collection.
+	if !isNormalized(queryEmbedding) {
+		queryEmbedding = normalizeVector(queryEmbedding)
+	}
+
 	// For the remaining documents, get the most similar docs.
 	nMaxDocs, err := getMostSimilarDocs(ctx, queryEmbedding, filteredDocs, nResults)
 	if err != nil {
diff --git a/collection_test.go b/collection_test.go
index e37e511..0823748 100644
--- a/collection_test.go
+++ b/collection_test.go
@@ -461,7 +461,6 @@ func TestCollection_Delete(t *testing.T) {
 
 	// Check number of files in the persist directory
 	d, err := os.ReadDir(c.persistDirectory)
-
 	if err != nil {
 		t.Fatal("expected nil, got", err)
 	}
@@ -507,7 +506,6 @@ func TestCollection_Delete(t *testing.T) {
 	}
 
 	checkCount(0)
-
 }
 
 // Global var for assignment in the benchmark to avoid compiler optimizations.
@@ -566,7 +564,7 @@ func benchmarkCollection_Query(b *testing.B, n int, withContent bool) {
 	for j := 0; j < d; j++ {
 		qv[j] = r.Float32()
 	}
-	// Most embeddings are normalized, so we normalize this one too
+	// The document embeddings are normalized, so the query must be normalized too.
 	qv = normalizeVector(qv)
 
 	// Create collection