diff --git a/Eigen/src/SVD/BDCSVD.h b/Eigen/src/SVD/BDCSVD.h
index a5e309cc3..b90e375bc 100644
--- a/Eigen/src/SVD/BDCSVD.h
+++ b/Eigen/src/SVD/BDCSVD.h
@@ -58,9 +58,9 @@ struct traits<BDCSVD<MatrixType_, Options> > : svd_traits<MatrixType_, Options>
  *
  * This class first reduces the input matrix to bi-diagonal form using class UpperBidiagonalization,
  * and then performs a divide-and-conquer diagonalization. Small blocks are diagonalized using class JacobiSVD.
- * You can control the switching size with the setSwitchSize() method, default is 16.
- * For small matrice (<16), it is thus preferable to directly use JacobiSVD. For larger ones, BDCSVD is highly
- * recommended and can several order of magnitude faster.
+ * You can control the switching size with the setSwitchSize() method, default is 8.
+ * For small matrices (<8), it is thus preferable to directly use JacobiSVD. For larger ones, BDCSVD is highly
+ * recommended and can be several orders of magnitude faster.
  *
  * \warning this algorithm is unlikely to provide accurate result when compiled with unsafe math optimizations.
  * For instance, this concerns Intel's compiler (ICC), which performs such optimization by default unless
diff --git a/Eigen/src/SVD/BDCSVDImpl.h b/Eigen/src/SVD/BDCSVDImpl.h
index 49267393c..89b85a48d 100644
--- a/Eigen/src/SVD/BDCSVDImpl.h
+++ b/Eigen/src/SVD/BDCSVDImpl.h
@@ -47,7 +47,7 @@ class bdcsvd_impl {
   typedef Ref<ArrayXr> ArrayRef;
   typedef Ref<ArrayXi> IndicesRef;
 
-  bdcsvd_impl() : m_algoswap(16), m_compU(false), m_compV(false), m_numIters(0), m_info(Success) {}
+  bdcsvd_impl() : m_algoswap(8), m_compU(false), m_compV(false), m_numIters(0), m_info(Success) {}
 
   void allocate(Index diagSize, bool compU, bool compV);
 
diff --git a/benchmarks/SVD/CMakeLists.txt b/benchmarks/SVD/CMakeLists.txt
index 7c37ab742..661d4cc59 100644
--- a/benchmarks/SVD/CMakeLists.txt
+++ b/benchmarks/SVD/CMakeLists.txt
@@ -1 +1,2 @@
 eigen_add_benchmark(bench_svd bench_svd.cpp)
+eigen_add_benchmark(bench_bdcsvd_crossover bench_bdcsvd_crossover.cpp)
diff --git a/benchmarks/SVD/bench_bdcsvd_crossover.cpp b/benchmarks/SVD/bench_bdcsvd_crossover.cpp
new file mode 100644
index 000000000..af116eb3a
--- /dev/null
+++ b/benchmarks/SVD/bench_bdcsvd_crossover.cpp
@@ -0,0 +1,73 @@
+#include <benchmark/benchmark.h>
+#include <Eigen/Dense>
+
+using namespace Eigen;
+
+// Benchmark to find the optimal BDCSVD -> JacobiSVD crossover threshold.
+//
+// Sweeps setSwitchSize() over a range of values for various matrix sizes
+// to determine the best crossover point now that JacobiSVD has been optimized.
+
+using Mat = Matrix<double, Dynamic, Dynamic>;
+
+template <int Options>
+EIGEN_DONT_INLINE void do_compute(BDCSVD<Mat, Options>& svd, const Mat& A) {
+  svd.compute(A);
+}
+
+// Args: {matrix_size, switch_size}
+template <int Options>
+static void BM_BDCSVD_Crossover(benchmark::State& state) {
+  const Index n = state.range(0);
+  const int switchSize = static_cast<int>(state.range(1));
+  Mat A = Mat::Random(n, n);
+  BDCSVD<Mat, Options> svd(n, n);
+  svd.setSwitchSize(switchSize);
+  for (auto _ : state) {
+    do_compute(svd, A);
+    benchmark::DoNotOptimize(svd.singularValues().data());
+  }
+  state.SetItemsProcessed(state.iterations());
+}
+
+// Also benchmark JacobiSVD at the same sizes for direct comparison.
+template <int Options>
+static void BM_JacobiSVD_Ref(benchmark::State& state) {
+  const Index n = state.range(0);
+  Mat A = Mat::Random(n, n);
+  JacobiSVD<Mat, Options> svd(n, n);
+  for (auto _ : state) {
+    svd.compute(A);
+    benchmark::DoNotOptimize(svd.singularValues().data());
+  }
+  state.SetItemsProcessed(state.iterations());
+}
+
+// clang-format off
+
+// Matrix sizes that exercise the crossover region and beyond.
+// Switch sizes from 3 (minimum) to 64.
+#define CROSSOVER_ARGS \
+    ->Args({16, 3})->Args({16, 4})->Args({16, 6})->Args({16, 8})->Args({16, 12})->Args({16, 16}) \
+    ->Args({32, 3})->Args({32, 4})->Args({32, 6})->Args({32, 8})->Args({32, 12})->Args({32, 16})->Args({32, 24})->Args({32, 32}) \
+    ->Args({48, 3})->Args({48, 6})->Args({48, 8})->Args({48, 12})->Args({48, 16})->Args({48, 24})->Args({48, 32})->Args({48, 48}) \
+    ->Args({64, 3})->Args({64, 6})->Args({64, 8})->Args({64, 12})->Args({64, 16})->Args({64, 24})->Args({64, 32})->Args({64, 48})->Args({64, 64}) \
+    ->Args({96, 3})->Args({96, 8})->Args({96, 12})->Args({96, 16})->Args({96, 24})->Args({96, 32})->Args({96, 48})->Args({96, 64}) \
+    ->Args({128, 3})->Args({128, 8})->Args({128, 12})->Args({128, 16})->Args({128, 24})->Args({128, 32})->Args({128, 48})->Args({128, 64}) \
+    ->Args({256, 3})->Args({256, 8})->Args({256, 16})->Args({256, 24})->Args({256, 32})->Args({256, 48})->Args({256, 64}) \
+    ->Args({512, 8})->Args({512, 16})->Args({512, 24})->Args({512, 32})->Args({512, 48})->Args({512, 64})
+
+#define JACOBI_REF_SIZES \
+    ->Args({16})->Args({32})->Args({48})->Args({64})->Args({96})->Args({128})
+
+// With vectors (typical use case)
+BENCHMARK(BM_BDCSVD_Crossover<ComputeThinU | ComputeThinV>) CROSSOVER_ARGS ->Name("BDCSVD_ThinUV");
+BENCHMARK(BM_JacobiSVD_Ref<ComputeThinU | ComputeThinV>) JACOBI_REF_SIZES ->Name("JacobiSVD_ThinUV");
+
+// Values only
+BENCHMARK(BM_BDCSVD_Crossover<0>) CROSSOVER_ARGS ->Name("BDCSVD_ValuesOnly");
+BENCHMARK(BM_JacobiSVD_Ref<0>) JACOBI_REF_SIZES ->Name("JacobiSVD_ValuesOnly");
+
+#undef CROSSOVER_ARGS
+#undef JACOBI_REF_SIZES
+// clang-format on