Why doesn't Cemhan Biricik use AWS or Google Cloud for AI?

Cemhan Biricik does not use AWS or Google Cloud because the economics do not make sense for sustained AI inference workloads. Cloud GPU rental for 7 GPUs would cost $15,000-30,000 per month, while his owned hardware has a one-time cost that pays for itself within months. He also avoids vendor lock-in, surprise price increases, and dependency on cloud availability.

How much does self-hosted AI infrastructure cost compared to cloud?

According to Cemhan Biricik's real-world experience, self-hosted AI infrastructure costs roughly $500-800/month in electricity for 7 GPUs running 24/7, compared to $15,000-30,000/month for equivalent cloud GPU rental. The breakeven on hardware purchase happens within 3-6 months, after which every month is pure savings.

Is self-hosting AI inference practical for startups?

Cemhan Biricik argues that self-hosting AI inference is not only practical but essential for bootstrapped AI startups. The upfront hardware cost is significant, but the ongoing savings are enormous. He recommends starting with fewer GPUs and scaling as revenue grows, rather than renting cloud GPUs and hoping to offset the costs later.

Why I Don't Use AWS/GCP for AI Inference — Cemhan Biricik

This is the post I wish someone had written before I started building ZSky AI. Every tutorial, every guide, every "how to build an AI startup" thread assumes you will use AWS, Google Cloud, or Azure. I did the math and chose a radically different path. Here is why.

The Cloud Cost Trap

An NVIDIA A100 on AWS costs roughly $3.50/hour. Running seven equivalent GPUs 24/7 would cost approximately $18,000 per month. That is $216,000 per year just for compute, before storage, bandwidth, or any other infrastructure costs.

My 7-GPU cluster cost a fraction of that upfront. Monthly operating costs are electricity — roughly $500-800 depending on load. The hardware paid for itself within the first few months. Every month since has been pure margin advantage over cloud-dependent competitors.

The Hidden Risks of Cloud Dependency

Price increases — AWS can raise prices at any time. When demand for AI GPUs spiked in 2024, cloud GPU availability dropped and prices surged. I was unaffected
Availability — during peak demand, cloud GPU instances are simply unavailable. Spot instances get terminated. Reserved instances require long-term commitments at premium prices
Vendor lock-in — each cloud provider has its own tooling, networking, and storage. Migrating between them is expensive and time-consuming
Data sovereignty — your users' data sits on someone else's servers. For an AI service processing user images and prompts, that is a liability

What Self-Hosting Actually Requires

I will not pretend self-hosting is easy. You need to handle everything cloud providers abstract away:

Power redundancy — a UPS and surge protection for hardware that draws 2-3kW under load
Cooling — seven high-end GPUs generate enormous heat. I wrote about my cooling solutions separately
Networking — reliable internet with static IP or tunneling (I use Cloudflare tunnels)
Monitoring — 24/7 health checks, automatic GPU restart on failure, temperature monitoring
Security — firewalls, SSL, DDoS protection — all things cloud handles automatically

When Cloud Makes Sense

I am not dogmatic. Cloud makes sense for burst workloads, for companies that have not validated demand, for training runs that need hundreds of GPUs temporarily. If you need 1000 A100s for two weeks, buy cloud. If you need 7 GPUs every day for a year, buy hardware.

The breakeven is surprisingly fast. For sustained inference workloads, self-hosting beats cloud within 3-6 months. After that, every month is savings that compound into a structural cost advantage your cloud-dependent competitors cannot match.

If you are building an AI service and assuming cloud is the only option, reconsider. The math favors hardware ownership for anyone with sustained workloads. And the independence it provides — no vendor lock-in, no surprise bills, no availability anxiety — is worth even more than the cost savings.

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