Question: I want to use my GPU for Tensorflow. I tried this Could not load dynamic library 'cudart64_101.dll' on tensorflow CPU-only installation Unfortunately, I keep getting an error Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found. How can I fix this? Python-version: 3.8.3, CUDA 10.1 2020-11-03 12:30:28.832014: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 2020-11-03 12:30:28.832688: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found 2020-11-03 12:30:28.833342: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found 2020-11-03 12:30:28.833994: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found 2020-11-03 12:30:28.834645: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found 2020-11-03 12:30:28.835297: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found 2020-11-03 12:30:28.835948: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found 2020-11-03 12:30:28.836594: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found 2020-11-03 12:30:28.836789: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1761] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform. Skipping registering GPU devices... 2020-11-03 12:30:28.837575: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2020-11-03 12:30:28.838495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1265] Device interconnect StreamExecutor with strength 1 edge matrix: 2020-11-03 12:30:28.838708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1271] 2020-11-03 12:30:28.838831: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 

Answer: Well, you can see that your Tensorflow installation is looking for Cuda libraries of version 11, 10, while you have 10.1. So in order to fix this, install the proper Cuda version. Why is it looking for 3 different versions, I have no idea. But you can find valid combinations of Cuda, Tensorflow, and CUDNN here. EDIT: Removed 8 from the Cuda version, Tensorflow is actually looking for CUDNN version 8. So don't forget to install CUDNN as well (my guess is that you are installing the latest version of Tensorflow -> that's why is it looking for the latest Cuda and CUDNN releases.)