diff --git a/ggml/src/ggml-zdnn/ggml-zdnn-rewrite.cpp b/ggml/src/ggml-zdnn/ggml-zdnn-rewrite.cpp
index 2f4e0d8491..767b33df0f 100644
--- a/ggml/src/ggml-zdnn/ggml-zdnn-rewrite.cpp
+++ b/ggml/src/ggml-zdnn/ggml-zdnn-rewrite.cpp
@@ -129,11 +129,7 @@ static void ggml_zdnn_mul_mat_op(ggml_backend_zdnn_context * ctx, const ggml_ten
     const int64_t output_rows = ne1;
     const int64_t output_cols = ne0;
 
-    const int64_t weights_dim[GGML_MAX_DIMS] = { 1, 1, weights_cols, weights_rows };
-    const int64_t inputs_dim[GGML_MAX_DIMS]  = { 1, 1, inputs_cols,  inputs_rows };
     const int64_t bias_dim  [GGML_MAX_DIMS]  = { 1, 1, 1, output_cols };
-    const int64_t output_dim[GGML_MAX_DIMS]  = { 1, 1, output_cols, output_rows };
-
     ggml_zdnn_create_tensor(ptd_bias, td_bias, zt_bias, output, bias_dim, ZDNN_1D);
 
     void * bias_data = (void *)calloc(ne0, ggml_element_size(output));
@@ -277,13 +273,12 @@ static bool ggml_zdnn_supports_op(const ggml_backend_zdnn_device_context * ctx_d
                 const int64_t ne0 = op->ne[0];
                 const int64_t ne1 = op->ne[1];
 
-                const int64_t max_batch = zdnn_get_nnpa_max_dim_idx_size();
+                const int64_t max_batch = ctx_dev->max_size;
 
                 return ggml_is_contiguous(src0) &&
                        ggml_is_contiguous(src1) &&
-                       src1->type == GGML_TYPE_F32 &&
-                       (ne0 <= max_batch && ne1 <= max_batch && ne10 <= max_batch) &&
-                       (src0->type == GGML_TYPE_F32 || ggml_get_type_traits(src0->type)->to_float != NULL);
+                       src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 &&
+                       (ne0 <= max_batch && ne1 <= max_batch && ne10 <= max_batch);
             } break;
 
         default: