diff --git a/tests/stress_tests/.automation/memcheck_tests/nightly_configs/desktop_test_config.xml b/tests/stress_tests/.automation/memcheck_tests/nightly_configs/desktop_test_config.xml
index 06573bd20ef..3d88499bcbd 100644
--- a/tests/stress_tests/.automation/memcheck_tests/nightly_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/memcheck_tests/nightly_configs/desktop_test_config.xml
@@ -6,77 +6,69 @@
     <models>
         <!--Models with FP32 precision-->
         <model name="mobilenet-v2-1.4-224" precision="FP32" source="omz" />
-        <model name="brain-tumor-segmentation-0001" precision="FP32" source="omz" />
+        <model name="brain-tumor-segmentation-0002" precision="FP32" source="omz" />
         <model name="faster_rcnn_inception_resnet_v2_atrous_coco" precision="FP32" source="omz" />
         <model name="yolo-v2-tf" precision="FP32" source="omz" />
-        <model name="se-inception" precision="FP32" source="omz" />
+        <model name="convnext-tiny" precision="FP32" source="omz" />
         <model name="efficientnet-b0" precision="FP32" source="omz" />
         <model name="mobilenet-v1-1.0-224-tf" precision="FP32" source="omz" />
         <model name="mask_rcnn_resnet50_atrous_coco" precision="FP32" source="omz" />
         <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
         <model name="googlenet-v3" precision="FP32" source="omz" />
-        <model name="alexnet" precision="FP32" source="omz" />
         <model name="googlenet-v4-tf" precision="FP32" source="omz" />
-        <model name="ssd300" precision="FP32" source="omz" />
-        <model name="vgg19" precision="FP32" source="omz" />
-        <model name="googlenet-v1" precision="FP32" source="omz" />
-        <model name="yolo-v3-tf" precision="FP32" source="omz" />
-        <model name="mtcnn-o" precision="FP32" source="omz" />
-        <model name="yolo-v1-tiny-tf" precision="FP32" source="omz" />
+        <model name="pedestrian-and-vehicle-detector-adas-0001" precision="FP32" source="omz" />
+        <model name="mixnet-l" precision="FP32" source="omz" />
         <model name="googlenet-v1-tf" precision="FP32" source="omz" />
+        <model name="yolo-v3-tf" precision="FP32" source="omz" />
+        <model name="face-reidentification-retail-0095" precision="FP32" source="omz" />
+        <model name="yolo-v1-tiny-tf" precision="FP32" source="omz" />
         <model name="yolo-v2-tiny-tf" precision="FP32" source="omz" />
-        <model name="ssd512" precision="FP32" source="omz" />
-        <model name="brain-tumor-segmentation-0002" precision="FP32" source="omz" />
-        <model name="Sphereface" precision="FP32" source="omz" />
-        <model name="googlenet-v2" precision="FP32" source="omz" />
+        <model name="pedestrian-detection-adas-0002" precision="FP32" source="omz" />
+        <model name="face-detection-retail-0004" precision="FP32" source="omz" />
+        <model name="googlenet-v2-tf" precision="FP32" source="omz" />
         <model name="ctdet_coco_dlav0_512" precision="FP32" source="omz" />
         <model name="ctpn" precision="FP32" source="omz" />
         <model name="i3d-rgb-tf" precision="FP32" source="omz" />
-        <model name="mobilenet-v2" precision="FP32" source="omz" />
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
-        <model name="se-resnext-50" precision="FP32" source="omz" />
-        <model name="caffenet" precision="FP32" source="omz" />
-        <model name="mtcnn-r" precision="FP32" source="omz" />
-        <model name="se-resnet-50" precision="FP32" source="omz" />
-        <model name="densenet-121" precision="FP32" source="omz" />
+        <model name="ssdlite_mobilenet_v2" precision="FP32" source="omz" />
+        <model name="resnest-50-pytorch" precision="FP32" source="omz" />
+        <model name="levit-128s" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
+        <model name="resnet-50-pytorch" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
         <model name="action-recognition-0001-decoder" precision="FP32" source="omz" />
         <model name="action-recognition-0001-encoder" precision="FP32" source="omz" />
         <model name="driver-action-recognition-adas-0002-decoder" precision="FP32" source="omz" />
         <!--Models with FP16 precision-->
         <model name="mobilenet-v2-1.4-224" precision="FP16" source="omz" />
-        <model name="brain-tumor-segmentation-0001" precision="FP16" source="omz" />
+        <model name="brain-tumor-segmentation-0002" precision="FP16" source="omz" />
         <model name="faster_rcnn_inception_resnet_v2_atrous_coco" precision="FP16" source="omz" />
         <model name="yolo-v2-tf" precision="FP16" source="omz" />
-        <model name="se-inception" precision="FP16" source="omz" />
+        <model name="convnext-tiny" precision="FP16" source="omz" />
         <model name="efficientnet-b0" precision="FP16" source="omz" />
         <model name="mobilenet-v1-1.0-224-tf" precision="FP16" source="omz" />
         <model name="mask_rcnn_resnet50_atrous_coco" precision="FP16" source="omz" />
         <model name="ssd_mobilenet_v1_coco" precision="FP16" source="omz" />
         <model name="googlenet-v3" precision="FP16" source="omz" />
-        <model name="alexnet" precision="FP16" source="omz" />
         <model name="googlenet-v4-tf" precision="FP16" source="omz" />
-        <model name="ssd300" precision="FP16" source="omz" />
-        <model name="vgg19" precision="FP16" source="omz" />
-        <model name="googlenet-v1" precision="FP16" source="omz" />
-        <model name="yolo-v3-tf" precision="FP16" source="omz" />
-        <model name="mtcnn-o" precision="FP16" source="omz" />
-        <model name="yolo-v1-tiny-tf" precision="FP16" source="omz" />
+        <model name="pedestrian-and-vehicle-detector-adas-0001" precision="FP16" source="omz" />
+        <model name="mixnet-l" precision="FP16" source="omz" />
         <model name="googlenet-v1-tf" precision="FP16" source="omz" />
+        <model name="yolo-v3-tf" precision="FP16" source="omz" />
+        <model name="face-reidentification-retail-0095" precision="FP16" source="omz" />
+        <model name="yolo-v1-tiny-tf" precision="FP16" source="omz" />
         <model name="yolo-v2-tiny-tf" precision="FP16" source="omz" />
-        <model name="ssd512" precision="FP16" source="omz" />
-        <model name="brain-tumor-segmentation-0002" precision="FP16" source="omz" />
-        <model name="Sphereface" precision="FP16" source="omz" />
-        <model name="googlenet-v2" precision="FP16" source="omz" />
+        <model name="pedestrian-detection-adas-0002" precision="FP16" source="omz" />
+        <model name="face-detection-retail-0004" precision="FP16" source="omz" />
+        <model name="googlenet-v2-tf" precision="FP16" source="omz" />
         <model name="ctdet_coco_dlav0_512" precision="FP16" source="omz" />
         <model name="ctpn" precision="FP16" source="omz" />
         <model name="i3d-rgb-tf" precision="FP16" source="omz" />
-        <model name="mobilenet-v2" precision="FP16" source="omz" />
-        <model name="mobilenet-ssd" precision="FP16" source="omz" />
-        <model name="se-resnext-50" precision="FP16" source="omz" />
-        <model name="caffenet" precision="FP16" source="omz" />
-        <model name="mtcnn-r" precision="FP16" source="omz" />
-        <model name="se-resnet-50" precision="FP16" source="omz" />
-        <model name="densenet-121" precision="FP16" source="omz" />
+        <model name="ssdlite_mobilenet_v2" precision="FP16" source="omz" />
+        <model name="resnest-50-pytorch" precision="FP16" source="omz" />
+        <model name="levit-128s" precision="FP16" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP16" source="omz" />
+        <model name="resnet-50-pytorch" precision="FP16" source="omz" />
+        <model name="densenet-121-tf" precision="FP16" source="omz" />
         <model name="action-recognition-0001-decoder" precision="FP16" source="omz" />
         <model name="action-recognition-0001-encoder" precision="FP16" source="omz" />
         <model name="driver-action-recognition-adas-0002-decoder" precision="FP16" source="omz" />
@@ -106,4 +98,4 @@
         <model name="yolo-v2-ava-0001" precision="FP16-INT8" source="omz" />
         <model name="person-detection-action-recognition-0005" precision="FP16-INT8" source="omz" />
     </models>
-</attributes>
\ No newline at end of file
+</attributes>
diff --git a/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml b/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
index cca3ec23df1..eb7b7a0ad79 100644
--- a/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
@@ -1,27 +1,27 @@
 <cases>
 
     <device name="CPU" iterations="1000" processes="1" threads="1">
-        <model name="alexnet" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
     </device>
 
     <device name="CPU" iterations="1000" processes="1" threads="1">
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
+        <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
     </device>
 
     <device name="CPU" iterations="1000" processes="1" threads="1">
-        <model name="mtcnn-r" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
     </device>
 
     <device name="GPU" iterations="1000" processes="1" threads="1">
-        <model name="alexnet" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
     </device>
 
     <device name="GPU" iterations="1000" processes="1" threads="1">
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
+        <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
     </device>
 
     <device name="GPU" iterations="1000" processes="1" threads="1">
-        <model name="mtcnn-r" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
     </device>
 
     <device name="CPU" iterations="1000" processes="1" threads="1">
@@ -33,15 +33,15 @@
     </device>
 
     <device name="CPU" iterations="1000" processes="1" threads="1">
-        <model name="alexnet" precision="FP32" source="omz" />
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
-        <model name="mtcnn-r" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
+        <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
     </device>
 
     <device name="GPU" iterations="1000" processes="1" threads="1">
-        <model name="alexnet" precision="FP32" source="omz" />
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
-        <model name="mtcnn-r" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
+        <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
     </device>
 
 </cases>
diff --git a/tests/stress_tests/.automation/unittests/nightly_configs/desktop_test_config.xml b/tests/stress_tests/.automation/unittests/nightly_configs/desktop_test_config.xml
index fc2ed5cba5c..603a6089468 100644
--- a/tests/stress_tests/.automation/unittests/nightly_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/unittests/nightly_configs/desktop_test_config.xml
@@ -15,8 +15,8 @@
         <value>GPU</value>
     </devices>
     <models>
-        <model name="alexnet" precision="FP32" source="omz" />
-        <model name="mobilenet-ssd" precision="FP32" source="omz" />
-        <model name="mtcnn-r" precision="FP32" source="omz" />
+        <model name="densenet-121-tf" precision="FP32" source="omz" />
+        <model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
+        <model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
     </models>
-</attributes>
\ No newline at end of file
+</attributes>