diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
index 414e14f85..1521e508c 100644
--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
@@ -6001,6 +6001,11 @@ bool ggml_vk_dim01_contiguous(const ggml_tensor * tensor) {
         (tensor->ne[3] == 1 || tensor->nb[3] == tensor->nb[2]*tensor->ne[2]);
 }
 
+// Batch stride in elements of a tensor read in place.
+static uint32_t ggml_vk_batch_stride(const ggml_tensor * tensor) {
+    return (uint32_t)(tensor->nb[2] / ggml_type_size(tensor->type) * ggml_blck_size(tensor->type));
+}
+
 vk_pipeline ggml_vk_get_cpy_pipeline(ggml_backend_vk_context * ctx, const ggml_tensor * src, const ggml_tensor * dst, ggml_type to) {
 
     // Choose "contiguous copy" shader if src/dst are contiguous
@@ -6488,8 +6493,13 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
         }
     }
 
-    uint32_t stride_batch_x = ne00*ne01;
-    uint32_t stride_batch_y = ne10*ne11;
+    // The partial tiles of a quantized A rely on the bound range to read zeros past the last row,
+    // so the range stays exact: the strided extent of a tensor read in place, the staged size otherwise.
+    const uint64_t x_range = qx_needs_dequant ? x_sz : ggml_nbytes(src0);
+    const uint64_t y_range = (qy_needs_dequant || quantize_y) ? y_sz : ggml_nbytes(src1);
+
+    uint32_t stride_batch_x = qx_needs_dequant ? ne00*ne01 : ggml_vk_batch_stride(src0);
+    uint32_t stride_batch_y = (qy_needs_dequant || quantize_y) ? ne10*ne11 : ggml_vk_batch_stride(src1);
 
     if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) {
         stride_batch_x = src0->nb[0] / ggml_type_size(src0->type);
@@ -6502,7 +6512,7 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
     // compute
     ggml_vk_matmul(
         ctx, subctx, pipeline,
-        { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz },
+        { d_X, x_buf_offset, x_range }, { d_Y, y_buf_offset, y_range },
         ggml_vk_subbuffer(ctx, d_D, d_buf_offset), { ctx->prealloc_split_k, 0, d_sz * split_k },
         ne01, ne11, ne10,
         ne10, ne10, stride_d, stride_batch_x, stride_batch_y, stride_batch_d,
@@ -6770,8 +6780,8 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context&
     }
 
     // For batch_n, the A matrix is the same for each batch, and B/D use the row stride as the batch stride
-    uint32_t stride_batch_x = batch_n ? 0 : ne00*ne01;
-    uint32_t stride_batch_y = batch_n ? ne10 : (ne10*ne11);
+    uint32_t stride_batch_x = batch_n ? 0 : (qx_needs_dequant ? ne00*ne01 : ggml_vk_batch_stride(src0));
+    uint32_t stride_batch_y = batch_n ? ne10 : ((qy_needs_dequant || quantize_y) ? ne10*ne11 : ggml_vk_batch_stride(src1));
     uint32_t stride_batch_d = batch_n ? ne20 : (ne20*ne21);
 
     if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) {
@@ -7601,9 +7611,12 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     }
     ggml_vk_sync_buffers(ctx, subctx);
 
-    uint32_t stride_batch_x = ne00*ne01;
+    const uint64_t x_range = qx_needs_dequant ? x_sz : ggml_nbytes(src0);
+    const uint64_t y_range = (qy_needs_dequant || quantize_y) ? y_sz : ggml_nbytes(src1);
+
+    uint32_t stride_batch_x = qx_needs_dequant ? ne00*ne01 : ggml_vk_batch_stride(src0);
     uint32_t stride_b_y = y_needs_k_padding ? y_staged_row_stride : ne10;
-    uint32_t stride_batch_y = y_needs_k_padding ? y_staged_row_stride * ne11 : ne10*ne11;
+    uint32_t stride_batch_y = y_needs_k_padding ? y_staged_row_stride * ne11 : ((qy_needs_dequant || quantize_y) ? ne10*ne11 : ggml_vk_batch_stride(src1));
 
     if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) {
         stride_batch_x = src0->nb[0] / ggml_type_size(src0->type);
@@ -7616,7 +7629,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     // compute
     ggml_vk_matmul_id(
         ctx, subctx, pipeline,
-        { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz },
+        { d_X, x_buf_offset, x_range }, { d_Y, y_buf_offset, y_range },
         { d_D, d_buf_offset, d_sz }, { d_ids, ids_buf_offset, ids_sz }, expert_count_buf,
         ne01, ne21, ne10, ne10, stride_b_y, ne01,
         stride_batch_x, stride_batch_y, ne20*ne21,
@@ -7801,7 +7814,8 @@ static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_conte
         }
     }
 
-    uint32_t stride_batch_y = ne10*ne11;
+    uint32_t stride_batch_x = qx_needs_dequant ? ne00*ne01 : ggml_vk_batch_stride(src0);
+    uint32_t stride_batch_y = (qy_needs_dequant || quantize_y) ? ne10*ne11 : ggml_vk_batch_stride(src1);
 
     if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) {
         stride_batch_y = src1->nb[2] / ggml_type_size(src1->type);
@@ -7844,7 +7858,7 @@ static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_conte
     for (uint32_t expert_i1 = 0; expert_i1 < nei1; ++expert_i1) {
         const vk_mat_vec_id_push_constants pc = {
             (uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01,
-            (uint32_t)(ne00 * ne01), stride_batch_y, (uint32_t)(ne20 * ne21),
+            stride_batch_x, stride_batch_y, (uint32_t)(ne20 * ne21),
             fusion_flags,
             (uint32_t)nei0, (uint32_t)ne11, expert_i1, nbi1
         };