Ignoring gpu device with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5. · Issue #4002 · tensorflow/tensorflow · GitHub
![UBUNTU 16.04] Tensorflow-gpu 1.11 with Compute capability 3.0 (with cuda 9 and cudnn 7.3) - GalaxySofts UBUNTU 16.04] Tensorflow-gpu 1.11 with Compute capability 3.0 (with cuda 9 and cudnn 7.3) - GalaxySofts](https://i0.wp.com/www.galaxysofts.com/new/wp-content/uploads/2018/10/aa.png)
UBUNTU 16.04] Tensorflow-gpu 1.11 with Compute capability 3.0 (with cuda 9 and cudnn 7.3) - GalaxySofts
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Install Tensorflow-GPU 2.0 with CUDA v10.0, cuDNN v7.6.5 for CUDA 10.0 on Windows 10 with NVIDIA Geforce GTX 1660 Ti. | by Suryatej MSKP | Medium
TensorFlow Performance with 1-4 GPUs -- RTX Titan, 2080Ti, 2080, 2070, GTX 1660Ti, 1070, 1080Ti, and Titan V
GitHub - sowmyyav/Tensorflow-gpu-ge1080: Install Tensorflow-GPU on Windows 10 with GEForce GTX1080, CUDA 11.2 and cuDNN 8.1
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The Simple Guide: Deep Learning with RTX 3090 (CUDA, cuDNN, Tensorflow, Keras, PyTorch) | by DeepLearnCH | Medium
![python - GPU Compute Capability 3.0 but the minimum required Cuda capability is 3.5 - Stack Overflow python - GPU Compute Capability 3.0 but the minimum required Cuda capability is 3.5 - Stack Overflow](https://i.stack.imgur.com/Ivf7O.png)