diff --git a/ggml/src/ggml-backend.cpp b/ggml/src/ggml-backend.cpp
index 20bf96501..273dc92b2 100644
--- a/ggml/src/ggml-backend.cpp
+++ b/ggml/src/ggml-backend.cpp
@@ -1372,30 +1372,6 @@ void ggml_backend_sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgra
                 const int src_backend_id = sched->hv_tensor_backend_ids[src_id];
                 GGML_ASSERT(src_backend_id != -1); // all inputs should be assigned by now
 
-                if (src->flags & GGML_TENSOR_FLAG_INPUT && sched->n_copies > 1) {
-                    if (tensor_id_copy(src_id, src_backend_id, 0) == NULL) {
-                        ggml_backend_t backend = sched->backends[src_backend_id];
-                        for (int c = 0; c < sched->n_copies; c++) {
-                            struct ggml_tensor * tensor_copy;
-                            if (c == sched->cur_copy) {
-                                tensor_copy = src; // use the original tensor as the current copy
-                            } else {
-                                tensor_copy = ggml_dup_tensor_layout(sched->ctx, src);
-                                ggml_format_name(tensor_copy, "%s#%s#%d", ggml_backend_name(backend), src->name, c);
-                            }
-                            ggml_set_input(tensor_copy);
-                            ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor
-                            tensor_id_copy(src_id, src_backend_id, c) = tensor_copy;
-                            SET_CAUSE(tensor_copy, "4.cpy");
-                        }
-                        int n_graph_inputs = sched->n_graph_inputs++;
-                        if (n_graph_inputs >= sched->graph_inputs_capacity) {
-                            ggml_backend_sched_graph_inputs_grow(sched);
-                        }
-                        sched->graph_inputs[n_graph_inputs] = src;
-                    }
-                }
-
                 if (src_backend_id != cur_backend_id && !ggml_backend_sched_buffer_supported(sched, src, cur_backend_id)) {
                     // create a copy of the input in the split's backend
                     if (tensor_id_copy(src_id, cur_backend_id, 0) == NULL) {
@@ -1428,6 +1404,46 @@ void ggml_backend_sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgra
         ggml_backend_sched_print_assignments(sched, graph);
     }
 
+    // pass 6: collect all input tensors into graph_inputs
+    //         this includes inputs not consumed by any node (e.g. the embeddings input of a text-only batch) so that
+    //         the graph composition does not depend on which inputs are used, which would otherwise cause graph
+    //         reallocations when switching between different types of batches [GGML_SCHED_DEBUG_REALLOC]
+    if (sched->n_copies > 1) {
+        for (int i = 0; i < graph->n_leafs; i++) {
+            struct ggml_tensor * leaf = graph->leafs[i];
+            if ((leaf->flags & GGML_TENSOR_FLAG_INPUT) == 0) {
+                continue;
+            }
+
+            const size_t leaf_id = hash_id(leaf);
+            const int leaf_backend_id = tensor_backend_id(leaf);
+            GGML_ASSERT(leaf_backend_id != -1); // all leafs should be assigned by now
+
+            if (tensor_id_copy(leaf_id, leaf_backend_id, 0) == NULL) {
+                ggml_backend_t backend = sched->backends[leaf_backend_id];
+                for (int c = 0; c < sched->n_copies; c++) {
+                    struct ggml_tensor * tensor_copy;
+                    if (c == sched->cur_copy) {
+                        tensor_copy = leaf; // use the original tensor as the current copy
+                    } else {
+                        tensor_copy = ggml_dup_tensor_layout(sched->ctx, leaf);
+                        ggml_format_name(tensor_copy, "%s#%s#%d", ggml_backend_name(backend), leaf->name, c);
+                    }
+                    ggml_set_input(tensor_copy);
+                    ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor
+                    tensor_id_copy(leaf_id, leaf_backend_id, c) = tensor_copy;
+                    SET_CAUSE(tensor_copy, "6.cpy");
+                }
+            }
+
+            int n_graph_inputs = sched->n_graph_inputs++;
+            if (n_graph_inputs >= sched->graph_inputs_capacity) {
+                ggml_backend_sched_graph_inputs_grow(sched);
+            }
+            sched->graph_inputs[n_graph_inputs] = leaf;
+        }
+    }
+
     // swap node_backend_ids and leaf _backend_ids with prevs
     {
         int * tmp = sched->node_backend_ids;