diff --git a/libavfilter/dnn/dnn_backend_torch.cpp b/libavfilter/dnn/dnn_backend_torch.cpp
index b70e4db600..0aa0b95269 100644
--- a/libavfilter/dnn/dnn_backend_torch.cpp
+++ b/libavfilter/dnn/dnn_backend_torch.cpp
@@ -37,8 +37,8 @@ extern "C" {
 }
 
 typedef struct THModel {
+    DNNModel model;
     DnnContext *ctx;
-    DNNModel *model;
     torch::jit::Module *jit_model;
     SafeQueue *request_queue;
     Queue *task_queue;
@@ -141,7 +141,7 @@ static void dnn_free_model_th(DNNModel **model)
     ff_queue_destroy(th_model->task_queue);
     delete th_model->jit_model;
     av_freep(&th_model);
-    av_freep(model);
+    *model = NULL;
 }
 
 static int get_input_th(void *model, DNNData *input, const char *input_name)
@@ -195,19 +195,19 @@ static int fill_model_input_th(THModel *th_model, THRequestItem *request)
     infer_request->input_tensor = new torch::Tensor();
     infer_request->output = new torch::Tensor();
 
-    switch (th_model->model->func_type) {
+    switch (th_model->model.func_type) {
     case DFT_PROCESS_FRAME:
         input.scale = 255;
         if (task->do_ioproc) {
-            if (th_model->model->frame_pre_proc != NULL) {
-                th_model->model->frame_pre_proc(task->in_frame, &input, th_model->model->filter_ctx);
+            if (th_model->model.frame_pre_proc != NULL) {
+                th_model->model.frame_pre_proc(task->in_frame, &input, th_model->model.filter_ctx);
             } else {
                 ff_proc_from_frame_to_dnn(task->in_frame, &input, ctx);
             }
         }
         break;
     default:
-        avpriv_report_missing_feature(NULL, "model function type %d", th_model->model->func_type);
+        avpriv_report_missing_feature(NULL, "model function type %d", th_model->model.func_type);
         break;
     }
     *infer_request->input_tensor = torch::from_blob(input.data,
@@ -282,13 +282,13 @@ static void infer_completion_callback(void *args) {
         goto err;
     }
 
-    switch (th_model->model->func_type) {
+    switch (th_model->model.func_type) {
     case DFT_PROCESS_FRAME:
         if (task->do_ioproc) {
             outputs.scale = 255;
             outputs.data = output->data_ptr();
-            if (th_model->model->frame_post_proc != NULL) {
-                th_model->model->frame_post_proc(task->out_frame, &outputs, th_model->model->filter_ctx);
+            if (th_model->model.frame_post_proc != NULL) {
+                th_model->model.frame_post_proc(task->out_frame, &outputs, th_model->model.filter_ctx);
             } else {
                 ff_proc_from_dnn_to_frame(task->out_frame, &outputs, th_model->ctx);
             }
@@ -298,7 +298,7 @@ static void infer_completion_callback(void *args) {
         }
         break;
     default:
-        avpriv_report_missing_feature(th_model->ctx, "model function type %d", th_model->model->func_type);
+        avpriv_report_missing_feature(th_model->ctx, "model function type %d", th_model->model.func_type);
         goto err;
     }
     task->inference_done++;
@@ -417,17 +417,10 @@ static DNNModel *dnn_load_model_th(DnnContext *ctx, DNNFunctionType func_type, A
     THRequestItem *item = NULL;
     const char *device_name = ctx->device ? ctx->device : "cpu";
 
-    model = (DNNModel *)av_mallocz(sizeof(DNNModel));
-    if (!model) {
-        return NULL;
-    }
-
     th_model = (THModel *)av_mallocz(sizeof(THModel));
-    if (!th_model) {
-        av_freep(&model);
+    if (!th_model)
         return NULL;
-    }
-    th_model->model = model;
+    model = &th_model->model;
     model->model = th_model;
     th_model->ctx = ctx;