title: What is the difference between tensorflow-gpu and tensorflow?
body: <p>When I see some tutorials regarding TensorFlow with GPU, it seems that the tutorial is using tensorflow-gpu instead of tensorflow.<br />
  The only info I got is the <a href="https://pypi.org/project/tensorflow-gpu/#:%7E:text=TensorFlow%20is%20an%20open%20source%20software%20library%20for%20high%20performance,to%20mobile%20and%20edge%20devices." rel="nofollow noreferrer">pypi page</a> where it doesn't cover much information.<br />
  Where the <a href="https://www.tensorflow.org/install/gpu" rel="nofollow noreferrer">official web</a> says that the tensorflow already packed with GPU support.</p>
  <p>So are there any differences between the two libraries?</p>
  <p>My hypothesis is in the early version tensorflow doesn't have native GPU support they create separate libraries, and the tensorflow-gpu is still updated for older users who already use tensorflow-gpu.</p>
  <p>[Update]<br />
  Thanks to the comment and the answers. I just finish installing several prerequisites related to Nvidia and use the plain TensorFlow and now I need to reinstall the CUDA version since the latest CUDA not compatible with the latest tensorflow. It's true that the setup can be a pain in the arse.</p>