Colab does not publish these limits, in part because they can (and sometimes do) vary quickly. This means that overall usage limits as well as idle timeout periods, maximum VM lifetime, GPU types available, and other factors vary over time. If you are interested in doing more in Colab than the resource limits of the free version of Colab allow, please try out Colab Pro and let us know what you think.Ĭolab is able to provide free resources in part by having dynamic usage limits that sometimes fluctuate, and by not providing guaranteed or unlimited resources. Our long term goal is to continue providing a free version of Colab, while also growing in a sustainable fashion to meet the needs of our users. Introducing Colab Pro is the first step we are taking towards serving users who want to do more in Colab.
We have heard from many users who want faster GPUs, longer running notebooks and more memory, as well as usage limits that are higher and don’t fluctuate as much. Some users want to be able to do more in Colab than the resource limits allow. Resources available in Colab vary over time to accommodate fluctuations in demand, as well as to accommodate overall growth and other factors. In order to be able to offer computational resources for free, Colab needs to maintain the flexibility to adjust usage limits and hardware availability on the fly. Why aren’t resources guaranteed in Colab?
Note that "deleting" files or subfolders by moving them to the Trash may not be enough if that doesn't seem to help, make sure to also Empty your Trash. Again, you can fix this problem by moving directly contained items into sub-folders. Accessing items in any folder containing many items can cause errors like OSError: Input/output error. A similar problem can occur when reading from other folders after a successful drive.mount(). If you encounter this problem, try moving files and folders directly contained in "My Drive" into sub-folders.
Repeated attempts may eventually succeed as failed attempts cache partial state locally before timing out. If thousands of items are directly contained in the top-level "My Drive" folder then mounting the drive will likely time out. Google Drive operations can time out when the number of files or subfolders in a folder grows too large.
Why does drive.mount() sometimes fail saying "timed out", and why do I/O operations in drive.mount()-mounted folders sometimes fail?
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