GPU time is the most expensive part of training or serving models — and also where a surprising amount of free capacity exists if you know where to look. Here are the legitimate ways to get free or near-free GPUs in 2026.
Recurring free GPU credits
- Modal — the free Starter plan includes $30 of compute every month, usable on GPU workloads, with one-click signup. This is the most practical recurring free GPU option for serverless jobs.
One-time GPU signup credits
Several inference and cloud hosts give credits on signup that you can spend on GPU-backed work:
- fal.ai — signup credits across image, video and GPU-compute models.
- Baseten — credits to deploy and test model inference on managed GPUs.
- DigitalOcean and OVHcloud — general cloud credits ($200 each) that can be applied to GPU droplets/instances where available.
See the full, dated list in the catalog.
Free GPU notebooks (great for experiments)
For research, fine-tuning experiments and learning, hosted notebooks remain the cheapest path:
- Google Colab and Kaggle both offer free GPU sessions, subject to availability and time limits.
- These are session-based, not dollar grants — perfect for trying an idea, not for production serving.
Free inference instead of raw GPUs
Often you do not actually need a raw GPU — you need model output. In that case, free LLM inference tiers from Cerebras, Groq and Gemini give you the result without managing any hardware at all. See How to Use AI for Free.
How to use free GPU time well
- Prototype on notebooks, then move to Modal's monthly credits for repeatable jobs.
- Right-size the GPU — many tasks run fine on a smaller, cheaper card.
- Watch idle time — free serverless platforms scale to zero; lean into that and avoid always-on instances.
- For serving, compare managed-inference prices before renting a GPU yourself; a specialized host on our rankings is often cheaper than DIY once you include ops time.
Claim the credits above with a free Perkstack account, and check the catalog for the current GPU and compute offers.