Nosana: Who Provides the GPUs?
In the previous post, we looked at what happens when you launch a GPU job on Nosana:
Job Definition → GPU Node → Container → Computation → Result
But where do those GPUs actually come from?
Nosana doesn’t need to own every GPU in the network.
Instead, GPU providers can contribute their own hardware and make it available for workloads.
This creates a simple two-sided model:
GPU providers → supply computing power
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AI developers → consume computing power
For GPU providers, hardware that would otherwise sit idle can become a source of revenue.
For AI developers, the same network can provide access to GPU capacity without having to purchase and maintain expensive hardware themselves.
This is one of the main ideas behind decentralized GPU infrastructure:
turn unused computing resources into a shared marketplace for AI workloads.
The interesting part is what happens when thousands of GPUs from different providers become part of the same network.
How can Nosana decide which GPU should run your job?
That’s where scheduling and GPU markets become important.
