diff --git a/whisper.cpp b/whisper.cpp
index e8d9f0c9..fbcba2c0 100644
--- a/whisper.cpp
+++ b/whisper.cpp
@@ -1457,7 +1457,7 @@ static bool whisper_encode(
                     layer.cross_attn_k_w,
                     cur);
 
-            Kcross = ggml_scale(ctx0, Kcross, ggml_new_f32(ctx0, pow(float(n_state)/n_head, -0.25)));
+            //Kcross = ggml_scale(ctx0, Kcross, ggml_new_f32(ctx0, pow(float(n_state)/n_head, -0.25)));
 
             struct ggml_tensor * Vcross = ggml_mul_mat(ctx0,
                     layer.cross_attn_v_w,
@@ -1579,14 +1579,14 @@ static bool whisper_decode(
                         Qcur),
                     Qcur);
 
-            Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
+            //Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
 
             // note: no bias for Key
             struct ggml_tensor * Kcur = ggml_mul_mat(ctxL,
                     layer.attn_k_w,
                     cur);
 
-            Kcur = ggml_scale(ctxL, Kcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
+            //Kcur = ggml_scale(ctxL, Kcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
 
             struct ggml_tensor * Vcur = ggml_mul_mat(ctxL,
                     layer.attn_v_w,
@@ -1609,6 +1609,33 @@ static bool whisper_decode(
 
             // ------
 
+#ifdef USE_FLASH_ATTN
+            struct ggml_tensor * Q =
+                ggml_permute(ctxL,
+                        ggml_cpy(ctxL,
+                            Qcur,
+                            ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
+                        0, 2, 1, 3);
+
+            struct ggml_tensor * K =
+                ggml_permute(ctxL,
+                        ggml_reshape_3d(ctxL,
+                            ggml_view_1d(ctxL, model.memory_k, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_k)*n_state),
+                            n_state/n_head, n_head, n_past + N),
+                        0, 2, 1, 3);
+
+            struct ggml_tensor * V =
+                ggml_cpy(ctxL,
+                        ggml_permute(ctxL,
+                            ggml_reshape_3d(ctxL,
+                                ggml_view_1d(ctxL, model.memory_v, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_v)*n_state),
+                                n_state/n_head, n_head, n_past + N),
+                            1, 2, 0, 3),
+                        ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_past + N, n_state/n_head, n_head)
+                        );
+
+            struct ggml_tensor * KQV = ggml_flash_attn(ctxL, Q, K, V, true);
+#else
             struct ggml_tensor * Q =
                 ggml_permute(ctxL,
                         ggml_cpy(ctxL,
@@ -1626,13 +1653,13 @@ static bool whisper_decode(
             // K * Q
             struct ggml_tensor * KQ = ggml_mul_mat(ctxL, K, Q);
 
-            //struct ggml_tensor * KQ_scaled =
-            //    ggml_scale(ctxL,
-            //            KQ,
-            //            ggml_new_f32(ctxL, 1.0f/sqrt(float(n_state)/n_head))
-            //            );
+            struct ggml_tensor * KQ_scaled =
+                ggml_scale(ctxL,
+                        KQ,
+                        ggml_new_f32(ctxL, 1.0f/sqrt(float(n_state)/n_head))
+                        );
 
-            struct ggml_tensor * KQ_masked = ggml_diag_mask_inf(ctxL, KQ, n_past);
+            struct ggml_tensor * KQ_masked = ggml_diag_mask_inf(ctxL, KQ_scaled, n_past);
 
             struct ggml_tensor * KQ_soft_max = ggml_soft_max(ctxL, KQ_masked);
 
@@ -1644,6 +1671,7 @@ static bool whisper_decode(
                         1, 2, 0, 3);
 
             struct ggml_tensor * KQV = ggml_mul_mat(ctxL, V_trans, KQ_soft_max);
+#endif
 
             struct ggml_tensor * KQV_merged = ggml_permute(ctxL, KQV, 0, 2, 1, 3);
 
@@ -1689,7 +1717,7 @@ static bool whisper_decode(
                         Qcur),
                     Qcur);
 
-            Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
+            //Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
 
             // Kcross is already scaled
             struct ggml_tensor * Kcross =
@@ -1704,6 +1732,24 @@ static bool whisper_decode(
 
             // ------
 
+#ifdef USE_FLASH_ATTN
+            struct ggml_tensor * Q =
+                ggml_permute(ctxL,
+                        ggml_cpy(ctxL,
+                            Qcur,
+                            ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
+                        0, 2, 1, 3);
+
+            struct ggml_tensor * K = ggml_permute(ctxL, Kcross, 0, 2, 1, 3);
+
+            struct ggml_tensor * V =
+                ggml_cpy(ctxL,
+                        ggml_permute(ctxL, Vcross, 1, 2, 0, 3),
+                        ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, M, n_state/n_head, n_head)
+                        );
+
+            struct ggml_tensor * KQV = ggml_flash_attn(ctxL, Q, K, V, false);
+#else
             struct ggml_tensor * Q =
                 ggml_permute(ctxL,
                         ggml_cpy(ctxL,
@@ -1730,6 +1776,7 @@ static bool whisper_decode(
             struct ggml_tensor * V_trans = ggml_permute(ctxL, Vcross, 1, 2, 0, 3);
 
             struct ggml_tensor * KQV = ggml_mul_mat(ctxL, V_trans, KQ_soft_max);
+#endif
 
             struct ggml_tensor * KQV_merged = ggml_permute(ctxL, KQV, 0, 2, 1, 3);