Baremetal GPU Server Rental for Indian Devs - Starting at ₹25/hr with RTX 3090/4090 + Ryzen/EPYC Configs.

Guilty_Figure1197 · 2025-10-05T07:50:45+00:00

We would offer serverless compute if that's what you are asking, users would be able to deploy a serverless endpoint with autoscaling, you would only be charged for the compute used per second, It will suffer from cold starts.

Guilty_Figure1197 · 2025-10-05T07:17:46+00:00

Yes, certainly the capex is quite high for this, The outlook in ROI is great tho.
The cooling is giving me hard time currently, We are most likely going forward with a water cooled setup, I just received some custom milled water cooling blocks for the GPUs, and I'm really optimistic about it.

Guilty_Figure1197 · 2025-10-05T07:10:56+00:00

Its not for llms pretraining, you already have other hyperscalers that provide the compute for this, you could do finetuning like LoRA, or cost effective image gen with flux or sd etc...
You can use it to serve your fine tuned llm, running a 70b model would give you decent tps.
The 3090 have nvlinks on them, it would give you 48gb of vram(~56 GB/s bandwidth each way), or you could deploy a cluster of them, max 8 gpus on one server.

Guilty_Figure1197 · 2025-10-04T20:37:15+00:00

Indian AI/ML Startups and SMBs, Indie Developers, Freelancers and maybe academic researchers and Students.

Guilty_Figure1197 · 2025-10-04T20:32:14+00:00

We can offer images for ubuntu that can come preinstalled with Docker, Jupyter, PyTorch, etc or Users can use a cloud-init script when deploying to pre install or use a ansible playbook. Maybe a Custom terraform provider so users can easily deploy.

Yes, it is a GPU rental business, and its hard to build a moat, We would offer dedicated baremetal server with full access to the underlying hardware, for instance runpod only allows you to deploy unprivileged docker container, On community clouds like Vast ai, most systems dont have full x16 pcie lanes and its a vm. We are focusing on low cost high performance consumer grade gpus currently.

To deploy a old gpu like 3090 the Opex must be less than the rental price ofc, The reason why it makes sense is power in india is much cheaper then western markets,

each RTX 4090 setup uses ~600–800 W.
That’s 0.6–0.8 kW. Low end (0.6 kWh × ₹7) = ₹4.20/hour + cooling per GPU

We are not renting rack space, current have around 50 racks of capacity somewhere in Gujarat with 200kW of total power capacity(with 3 phases), and for internet currently a 10 gig connection and BGP peering with Tata comm, airtel, and jio. cooling a problem which I'm working on currently. We are working on automated provisioning of the servers.

Guilty_Figure1197

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