Free GPU Resources for Students
For most course projects, you do not need to pay for a GPU. Between your own machine, the HIT lab computers, and several free cloud platforms, you can train and run most models at no cost.
Where to get a free GPU
Start local, move to the cloud when you need more compute.
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Your own PC or the HIT lab computers
No account neededIf your PC has a GPU, or you use the HIT lab machines (which have a 6 GB GPU), you can run many course workloads locally with no quota or sign-up. A 6 GB card handles small models, fine-tuning of compact models, and most course experiments; move to the cloud for anything larger.
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Free GPU/TPU
The simplest option. Runs Jupyter notebooks in the browser and provides free GPU/TPU access, subject to availability and usage limits.
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~30 GPU hrs/week
Free cloud notebooks with GPU access. Kaggle currently documents a GPU quota of about 30 hours per week, although quotas may vary.
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Monthly credits
Cloud development environment for AI projects. The free academic tier includes monthly credits for GPUs; Lightning states these can provide roughly 35–80 GPU hours, depending on the machine and pricing.
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$30 credit/month
Good when you need to run Python jobs on GPUs rather than work only inside notebooks. The Starter plan costs $0/month and includes $30 of compute credit each month for GPU workloads.
Recommendation: start with your own machine or the lab, then Colab or Kaggle. Move to Lightning AI or Modal when you need more compute, different GPUs, or a more flexible execution environment.
Free tiers, GPU types, and quotas change frequently, so check the current limits before starting a large experiment.