diff --git a/ggml/src/ggml-amx.cpp b/ggml/src/ggml-amx.cpp
index 25f46e77c74bf1..7494b0219e3676 100644
--- a/ggml/src/ggml-amx.cpp
+++ b/ggml/src/ggml-amx.cpp
@@ -188,36 +188,45 @@ static enum ggml_status ggml_backend_amx_graph_compute(ggml_backend_t backend, s
 
 static bool ggml_backend_amx_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
 
-  if (op->op != GGML_OP_MUL_MAT) {
-    return false;
-  }
+  // handle only 2d gemm for now
+  auto is_contiguous_2d = [](const struct ggml_tensor * t) {
+    return ggml_is_contiguous(t) && t->ne[3] == 1 && t->ne[2] == 1;
+  };
 
-  const struct ggml_tensor * src0 = op->src[0];
-  const struct ggml_tensor * src1 = op->src[1];
+  switch (op->op) {
+    case GGML_OP_NONE:
+    case GGML_OP_RESHAPE:
+    case GGML_OP_VIEW:
+    case GGML_OP_PERMUTE:
+    case GGML_OP_TRANSPOSE:
+      return true;
 
-  const enum ggml_type type = src0->type;
-  const int64_t ne0 = op->ne[0];
+    case GGML_OP_MUL_MAT: {
+      const struct ggml_tensor * src0 = op->src[0];
+      const struct ggml_tensor * src1 = op->src[1];
 
-  bool is_training = src0->grad || src1->grad;
+      const enum ggml_type type = src0->type;
+      const int64_t ne0 = op->ne[0];
 
-  // amx kernels enables for Q4_0, Q4_1, Q8_0, F16
-  // Q4_K, Q5_K, Q6_K, IQ4_XS enabled for QK_K = 256
-  bool has_amx_kernels = qtype_has_amx_kernels(type) || (type == GGML_TYPE_F16);
+      bool is_training = src0->grad || src1->grad;
 
-  // handle only 2d gemm for now
-  auto is_contiguous_2d = [](const struct ggml_tensor * t) {
-    return ggml_is_contiguous(t) && t->ne[3] == 1 && t->ne[2] == 1;
-  };
+      // amx kernels enables for Q4_0, Q4_1, Q8_0, F16
+      // Q4_K, Q5_K, Q6_K, IQ4_XS enabled for QK_K = 256
+      bool has_amx_kernels = qtype_has_amx_kernels(type) || (type == GGML_TYPE_F16);
 
-  bool can_use_amx =
-      is_contiguous_2d(src0) &&       // src0 must be contiguous
-      is_contiguous_2d(src1) &&       // src1 must be contiguous
-      !is_training &&                 // inference only
-      src1->type == GGML_TYPE_F32 &&  // src1 must be float32
-      has_amx_kernels &&              // with amx kernel impls
-      ne0 % (TILE_N * 2) == 0;        // out_features is 32x
+      bool can_use_amx =
+          is_contiguous_2d(src0) &&       // src0 must be contiguous
+          is_contiguous_2d(src1) &&       // src1 must be contiguous
+          !is_training &&                 // inference only
+          src1->type == GGML_TYPE_F32 &&  // src1 must be float32
+          has_amx_kernels &&              // with amx kernel impls
+          ne0 % (TILE_N * 2) == 0;        // out_features is 32x
 
-  return can_use_amx;
+      return can_use_amx;
+    }
+    default:
+      return false;
+  }
 
   GGML_UNUSED(backend);
 }
diff --git a/ggml/src/ggml-backend.cpp b/ggml/src/ggml-backend.cpp
index 0fa5004e443fbc..15d650150a5f34 100644
--- a/ggml/src/ggml-backend.cpp
+++ b/ggml/src/ggml-backend.cpp
@@ -1496,12 +1496,10 @@ static int ggml_backend_sched_backend_id_from_cur(ggml_backend_sched_t sched, st
         }
     }
 
-#ifndef GGML_USE_AMX
     if (tensor->buffer || (tensor->view_src && tensor->view_src->buffer)) {
         // since the tensor is pre-allocated, it cannot be moved to another backend
         GGML_ABORT("pre-allocated tensor in a backend that cannot run the operation");
     }
-#endif
 
     // graph input
     if (tensor->flags & GGML_TENSOR_FLAG_INPUT) {