diff --git a/hnswlib/bruteforce.h b/hnswlib/bruteforce.h
index 8727cc8a..371847ad 100644
--- a/hnswlib/bruteforce.h
+++ b/hnswlib/bruteforce.h
@@ -107,27 +107,17 @@ class BruteforceSearch : public AlgorithmInterface<dist_t> {
     searchKnn(const void *query_data, size_t k, BaseFilterFunctor* isIdAllowed = nullptr) const {
         assert(k <= cur_element_count);
         std::priority_queue<std::pair<dist_t, labeltype >> topResults;
-        if (cur_element_count == 0) return topResults;
-        for (int i = 0; i < k; i++) {
+        dist_t lastdist = std::numeric_limits<dist_t>::max();
+        for (int i = 0; i < cur_element_count; i++) {
             dist_t dist = fstdistfunc_(query_data, data_ + size_per_element_ * i, dist_func_param_);
-            labeltype label = *((labeltype*) (data_ + size_per_element_ * i + data_size_));
-            if ((!isIdAllowed) || (*isIdAllowed)(label)) {
-                topResults.emplace(dist, label);
-            }
-        }
-        dist_t lastdist = topResults.empty() ? std::numeric_limits<dist_t>::max() : topResults.top().first;
-        for (int i = k; i < cur_element_count; i++) {
-            dist_t dist = fstdistfunc_(query_data, data_ + size_per_element_ * i, dist_func_param_);
-            if (dist <= lastdist) {
+            if (dist <= lastdist || topResults.size() < k) {
                 labeltype label = *((labeltype *) (data_ + size_per_element_ * i + data_size_));
                 if ((!isIdAllowed) || (*isIdAllowed)(label)) {
                     topResults.emplace(dist, label);
-                }
-                if (topResults.size() > k)
-                    topResults.pop();
-
-                if (!topResults.empty()) {
-                    lastdist = topResults.top().first;
+                    if (topResults.size() > k)
+                        topResults.pop();
+                    if (!topResults.empty())
+                        lastdist = topResults.top().first;
                 }
             }
         }
diff --git a/python_bindings/bindings.cpp b/python_bindings/bindings.cpp
index dd09e80a..56ce9beb 100644
--- a/python_bindings/bindings.cpp
+++ b/python_bindings/bindings.cpp
@@ -871,16 +871,39 @@ class BFIndex {
             CustomFilterFunctor idFilter(filter);
             CustomFilterFunctor* p_idFilter = filter ? &idFilter : nullptr;
 
-            ParallelFor(0, rows, num_threads, [&](size_t row, size_t threadId) {
-                std::priority_queue<std::pair<dist_t, hnswlib::labeltype >> result = alg->searchKnn(
-                    (void*)items.data(row), k, p_idFilter);
-                for (int i = k - 1; i >= 0; i--) {
-                    auto& result_tuple = result.top();
-                    data_numpy_d[row * k + i] = result_tuple.first;
-                    data_numpy_l[row * k + i] = result_tuple.second;
-                    result.pop();
-                }
-            });
+            if (!normalize) {
+                ParallelFor(0, rows, num_threads, [&](size_t row, size_t threadId) {
+                    std::priority_queue<std::pair<dist_t, hnswlib::labeltype >> result = alg->searchKnn(
+                        (void*)items.data(row), k, p_idFilter);
+                    if (result.size() != k)
+                        throw std::runtime_error(
+                            "Cannot return the results in a contiguous 2D array. There are not enough elements.");
+                    for (int i = k - 1; i >= 0; i--) {
+                        auto& result_tuple = result.top();
+                        data_numpy_d[row * k + i] = result_tuple.first;
+                        data_numpy_l[row * k + i] = result_tuple.second;
+                        result.pop();
+                    }
+                });
+            } else {
+                std::vector<float> norm_array(num_threads * features);
+                ParallelFor(0, rows, num_threads, [&](size_t row, size_t threadId) {
+                    size_t start_idx = threadId * dim;
+                    normalize_vector((float*)items.data(row), norm_array.data() + start_idx);
+
+                    std::priority_queue<std::pair<dist_t, hnswlib::labeltype >> result = alg->searchKnn(
+                        (void*)(norm_array.data() + start_idx), k, p_idFilter);
+                    if (result.size() != k)
+                        throw std::runtime_error(
+                            "Cannot return the results in a contiguous 2D array. There are not enough elements.");
+                    for (int i = k - 1; i >= 0; i--) {
+                        auto& result_tuple = result.top();
+                        data_numpy_d[row * k + i] = result_tuple.first;
+                        data_numpy_l[row * k + i] = result_tuple.second;
+                        result.pop();
+                    }
+                });
+            }
         }
 
         py::capsule free_when_done_l(data_numpy_l, [](void *f) {