diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp
index 0ecd1a5107..ab6d4f0656 100644
--- a/ggml/src/ggml-metal/ggml-metal-ops.cpp
+++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp
@@ -273,7 +273,7 @@ static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) {
                         ggml_is_contiguous(node->src[3]), node->src[3]->name);
             }
             if (node) {
-                GGML_LOG_DEBUG("%s: node  - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(node->type), ne0, ne1, ne2, ne3, nb0, nb1, nb2, nb3,
+                GGML_LOG_DEBUG("%s: node - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(node->type), ne0, ne1, ne2, ne3, nb0, nb1, nb2, nb3,
                         node->name);
             }
         }
@@ -649,6 +649,8 @@ int ggml_metal_op_repeat(ggml_metal_op_t ctx, int idx) {
     GGML_TENSOR_LOCALS( int32_t, ne,  op,         ne);
     GGML_TENSOR_LOCALS(uint64_t, nb,  op,         nb);
 
+    // TODO: optimize for degenerate cases such as ggml_nelements(op->src[0]) == 1 and others
+
     auto pipeline = ggml_metal_library_get_pipeline_repeat(lib, op->type);
 
     ggml_metal_kargs_repeat args = {
diff --git a/src/models/qwen4exp.cpp b/src/models/qwen4exp.cpp
index cf8a487241..facab0ebfb 100644
--- a/src/models/qwen4exp.cpp
+++ b/src/models/qwen4exp.cpp
@@ -840,20 +840,22 @@ ggml_tensor * llama_model_qwen4exp::graph::build_qsa_sel(
     const int64_t n_sel = sel_idx->ne[0];
     GGML_ASSERT(n_sel == inp_kpool->n_sel);
 
+    ggml_build_forward_expand(gf, sel_idx);
+
     // TODO: figure out to reduce the large copmute buffer that this creates
+
     // scatter zeros for the selected cells into an all -inf row, each dead slot into its own dump row n_kv + slot
     // seeding from sel_idx ties the scatter storage lifetime to this layer
     const int64_t n_kv = inp_kpool->n_kv;
 
-    ggml_tensor * seed = ggml_cast(ctx0, ggml_view_1d(ctx0, sel_idx, 1, 0), GGML_TYPE_F32);
-
-    ggml_tensor * mask_seed = kq_mask->type == GGML_TYPE_F32 ? seed : ggml_cast(ctx0, seed, kq_mask->type);
-    mask_seed = ggml_fill(ctx0, mask_seed, -INFINITY);
-    ggml_tensor * mask_all = ggml_repeat_4d(ctx0, mask_seed, 1, n_kv + n_sel, n_tokens, 1);
+    ggml_tensor * mask_all = ggml_new_tensor_4d(ctx0, kq_mask->type, n_kv + n_sel, 1, 1, 1);
+    mask_all = ggml_fill(ctx0, mask_all, -INFINITY);
+    mask_all = ggml_repeat_4d(ctx0, mask_all, n_kv + n_sel, n_tokens, 1, 1);
     mask_all = ggml_reshape_3d(ctx0, mask_all, 1, n_kv + n_sel, n_tokens);
 
-    ggml_tensor * zero_seed = ggml_fill(ctx0, seed, 0.0f);
-    ggml_tensor * zeros = ggml_repeat_4d(ctx0, zero_seed, 1, n_sel, n_tokens, 1);
+    ggml_tensor * zeros = ggml_new_tensor_4d(ctx0, kq_mask->type, n_sel, 1, 1, 1);
+    zeros = ggml_fill(ctx0, zeros, 0.0f);
+    zeros = ggml_repeat_4d(ctx0, zeros, n_sel, n_tokens, 1, 1);
     zeros = ggml_reshape_3d(ctx0, zeros, 1, n_sel, n_tokens);
 
     // live slots address disjoint cells, but padded pools and missing tail cells share the n_kv sentinel, and