diff --git a/nn/runtime/test/generated/models/conv_quant8_overflow_weights_as_inputs.model.cpp b/nn/runtime/test/generated/models/conv_quant8_overflow_weights_as_inputs.model.cpp
new file mode 100644
index 0000000..8a3155f
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_quant8_overflow_weights_as_inputs.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: conv_quant8_overflow_weights_as_inputs.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type2(Type::TENSOR_INT32, {3}, 0.25, 0);
+  OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 0.5, 0);
+  OperandType type4(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 1.0, 0);
+  OperandType type1(Type::TENSOR_QUANT8_ASYMM, {3, 1, 1, 3}, 0.5, 0);
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type4);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}