diff --git a/extension/module/module.cpp b/extension/module/module.cpp
index 99cc7e38bd6..598c941bae9 100644
--- a/extension/module/module.cpp
+++ b/extension/module/module.cpp
@@ -125,32 +125,38 @@ runtime::Result<std::unordered_set<std::string>> Module::method_names() {
 
 runtime::Error Module::load_method(
     const std::string& method_name,
+    runtime::HierarchicalAllocator* planned_memory,
     torch::executor::EventTracer* event_tracer) {
   if (!is_method_loaded(method_name)) {
     ET_CHECK_OK_OR_RETURN_ERROR(load());
 
     MethodHolder method_holder;
-    const auto method_metadata =
+
+    if (!planned_memory) {
+      const auto method_metadata =
         ET_UNWRAP(program_->method_meta(method_name.c_str()));
-    const auto planned_buffersCount =
-        method_metadata.num_memory_planned_buffers();
-    method_holder.planned_buffers.reserve(planned_buffersCount);
-    method_holder.planned_spans.reserve(planned_buffersCount);
-
-    for (auto index = 0; index < planned_buffersCount; ++index) {
-      const auto buffer_size =
-          method_metadata.memory_planned_buffer_size(index).get();
-      method_holder.planned_buffers.emplace_back(buffer_size);
-      method_holder.planned_spans.emplace_back(
-          method_holder.planned_buffers.back().data(), buffer_size);
+      const auto planned_buffers_count =
+          method_metadata.num_memory_planned_buffers();
+      method_holder.planned_buffers.reserve(planned_buffers_count);
+      method_holder.planned_spans.reserve(planned_buffers_count);
+
+      for (auto index = 0; index < planned_buffers_count; ++index) {
+        const auto buffer_size =
+            method_metadata.memory_planned_buffer_size(index).get();
+        method_holder.planned_buffers.emplace_back(buffer_size);
+        method_holder.planned_spans.emplace_back(
+            method_holder.planned_buffers.back().data(), buffer_size);
+      }
+      method_holder.planned_memory =
+          std::make_unique<runtime::HierarchicalAllocator>(
+              runtime::Span(
+                  method_holder.planned_spans.data(),
+                  method_holder.planned_spans.size()));
+      planned_memory = method_holder.planned_memory.get();
     }
-    method_holder.planned_memory =
-        std::make_unique<runtime::HierarchicalAllocator>(runtime::Span(
-            method_holder.planned_spans.data(),
-            method_holder.planned_spans.size()));
     method_holder.memory_manager = std::make_unique<runtime::MemoryManager>(
         memory_allocator_.get(),
-        method_holder.planned_memory.get(),
+        planned_memory,
         temp_allocator_.get());
     method_holder.method = ET_UNWRAP_UNIQUE(program_->load_method(
         method_name.c_str(),
diff --git a/extension/module/module.h b/extension/module/module.h
index 45ed38a7ff2..737a8969e67 100644
--- a/extension/module/module.h
+++ b/extension/module/module.h
@@ -133,6 +133,8 @@ class Module {
    * needed. The loaded method is cached to reuse the next time it's executed.
    *
    * @param[in] method_name The name of the method to load.
+   * @param[in] planned_memory The memory-planned buffers to use for mutable
+   * tensor data when executing a method.
    * @param[in] event_tracer Per-method event tracer to profile/trace methods
    * individually. When not given, the event tracer passed to the Module
    * constructor is used. Otherwise, this per-method event tracer takes
@@ -143,20 +145,36 @@ class Module {
   ET_NODISCARD
   runtime::Error load_method(
       const std::string& method_name,
+      runtime::HierarchicalAllocator* planned_memory = nullptr,
       torch::executor::EventTracer* event_tracer = nullptr);
 
+  ET_DEPRECATED ET_NODISCARD
+  runtime::Error inline load_method(
+    const std::string& method_name,
+    torch::executor::EventTracer* event_tracer) {
+    return load_method(method_name, nullptr, event_tracer);
+  }
+
   /**
    * Load the 'forward' method from the program and set up memory management if
    * needed. The loaded method is cached to reuse the next time it's executed.
    *
+   * @param[in] planned_memory The memory-planned buffers to use for mutable
+   * tensor data when executing the 'forward' method.
    * @param[in] event_tracer An event tracer used for tracking and logging
    * events.
    *
    * @returns An Error to indicate success or failure.
    */
   ET_NODISCARD inline runtime::Error load_forward(
+      runtime::HierarchicalAllocator* planned_memory = nullptr,
       torch::executor::EventTracer* event_tracer = nullptr) {
-    return load_method("forward", event_tracer);
+    return load_method("forward", planned_memory, event_tracer);
+  }
+
+  ET_DEPRECATED ET_NODISCARD inline runtime::Error load_forward(
+      torch::executor::EventTracer* event_tracer) {
+    return load_forward(nullptr, event_tracer);
   }
 
   /**