diff --git a/docker/Dockerfile b/docker/Dockerfile
index be157f796..3e3371667 100644
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -3,7 +3,7 @@
 # Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference
 
 # Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch or nvcr.io/nvidia/pytorch:23.03-py3
-FROM pytorch/pytorch:2.2.2-cuda12.1-cudnn8-runtime
+FROM pytorch/pytorch:2.3.1-cuda12.1-cudnn8-runtime
 RUN pip install --no-cache-dir tensorrt
 
 # Set environment variables
diff --git a/docker/Dockerfile-conda b/docker/Dockerfile-conda
index 3eeb10879..0ab647bb0 100644
--- a/docker/Dockerfile-conda
+++ b/docker/Dockerfile-conda
@@ -20,7 +20,7 @@ ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt .
 # Install conda packages
 # mkl required to fix 'OSError: libmkl_intel_lp64.so.2: cannot open shared object file: No such file or directory'
 RUN conda config --set solver libmamba && \
-    conda install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia && \
+    conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \
     conda install -c conda-forge ultralytics mkl
     # conda install -c pytorch -c nvidia -c conda-forge pytorch torchvision pytorch-cuda=11.8 ultralytics mkl