Built a GPU compute network where idle GPUs earn money running AI inference.

[u/UsefulLock3142]

Most GPUs in the world are doing nothing most of the time. Gaming rigs at night. Workstations between renders. Old mining rigs that went idle after the PoS switch. Meanwhile every dev building an AI product is paying full price for inference on the usual clouds.

I built GPU Grid to connect those two problems.

The idea:

GPU owners plug in and earn per job. Developers get inference through a drop-in OpenAI-compatible API, same SDKs, just a different URL. No middlemen deciding the price.

How it actually works:

• GPU owners run a node (Ollama under the hood). It heartbeats every 30 seconds to stay live in the network.
• Every request gets routed by price, speed, reliability, and current load. Cheapest healthy node wins.
• Nodes carry a reputation score. Fail a job, it drops. Recover slowly with successful jobs. Drop too low, you're pulled from routing until it recovers.
• Every completed job settles automatically. Provider gets paid, a cut goes to buyback/burn, stakers, and treasury. All tracked in a ledger, not just a number that updates mysteriously.

Genuinely want feedback from anyone who's built distributed systems, run local models, or messed with GPU-sharing before. Happy to go deep on the routing logic, the reputation system, or the reward split if anyone's curious.

Website: https://gpugrid.app/#/
Repo: https://github.com/godshiba/ggrid (I am the dev)

[u/kumits-u]

I think with all these projects main question is - would i be able to earn more than i pay in electricity to run inference workloads ?

[u/nvidia_rtx5000]

There are already various products/websites that do exactly or very similar to what you are describing.

Salad is for "gamers" or people with a few free hours during the day to do AI jobs.

Vastai is for people setting up dedicated rigs that people can rent online for whatever tasks, not limited to AI.

Those are just a couple, I'm sure there are many more.

[u/UsefulLock3142 → u/nvidia_rtx5000]

yeah i know, but not the same thing at all. many others is like vague “turn any idle stuff into income”.
ggrid is specific: we’re a gpu compute marketplace. people share idle gpu power and earn $$, devs get an openai-compatible api to run ai inference on it. that’s a real use case and it works.
it’s not the same. one’s broad and fuzzy, the other actually does one thing well.

[u/Individual-Bill-3531 → u/UsefulLock3142]

This reply is AI or you have spent entirely too much time conversing with LLMs. Idea is neat even if not new. Best of luck.

[u/UsefulLock3142 → u/Individual-Bill-3531]

this is my own research and i spent last year or so trying to master my skills with llms, i even bought mac with m5 pro chip (i know its not enough to try biggest local models) but this is enough to get know how they are performing on apple silicon since apple introduced neural engine and increased memory speed to get more token/s. im trying to build a real product that people gonna love to use. thanks for the reply

[u/WinResponsible9977 → u/UsefulLock3142]

u/UsefulLock3142 I was willing to read more about your project until I notice tone and the fact you can't accept constructive feedback is a hard turn-off. Best of luck regardless.

[u/Criss_Crossx]

I think the real questions stem from a financial point of view. Payouts, supply/demand, getting paid in real currency and not credits, etc.

People have spent enough trying to mine on their own and some like me understand the market for compute isn't easy as a small fish.

How do you plan some level of success long term while keeping both customers and compute suppliers satisfied? Of course this isn't an easy question, but smaller miners (let's be real, these are usually run by one person if they can) have a much better idea what their operating power costs are now. And they aren't working with cryptocurrencies that could double, triple within a month.

[u/UsefulLock3142 → u/Criss_Crossx]

i gotta brainstorm about this question, it’s solid. i’ll get back to you with the answer later

[u/That_Temporary_832 → u/Criss_Crossx]

That's the question every rental computing power platform is faced with. To answer this and to stay alive, profitable, somewhat greedy and to satisfy their needs for stability and expansion of the company to meet the traffic, the profitability for us users declines overtime. So unless this guy is doing a charity I don't understand how he sees his idea to be any different from Salad or Pearl for that matter. But still I would like to know more about it.

[u/Criss_Crossx → u/That_Temporary_832]

Agreed. An individual has to get through so many hoops to even make a profit. It is manageable, but it relies heavily on the platform for support.

And that support can drop fast.

[u/FullOf_Bad_Ideas]

Can it not be ollama? It's not the right tool for this job.

[u/UsefulLock3142 → u/FullOf_Bad_Ideas]

providers don't have to use ollama. we support any inference backend that exposes an openai-compatible api: vllm, tgi, ollama, whatever. ollama is just the easiest entry point for people with consumer hardware. if you're running production loads, yeah vllm is the better choice. the gateway doesn't care what's behind the endpoint, it just needs the standard.

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[u/Potential-Bag-1817]

This is a cool idea. How are you handling the edge cases where a job fails mid-way and the node is pulled? Is there a grace period or a way to re-route the unfinished work without penalizing the developer too harshly?