How Much Does It Cost to Self-Host Open Models on AWS?
Your AI bill tripled last quarter. Your CTO forwarded you an article about companies saving 70% by switching to open models. Now someone is asking you to figure out what that would actually look like. I spent the last few weeks digging into this. The numbers, the hardware, the real trade-offs. Here's what I found, with enough specifics that you can actually make a decision rather than just…
Self-hosting open AI models on AWS can be surprisingly affordable compared to commercial options. The key factors are the size of the model and the hardware needed to run it efficiently.
Using state-of-the-art models like Llama 4 Maverick, which has 400 billion parameters, requires at least 4 GPUs with around 24 GB of VRAM each to run comfortably. A single AWS instance with 4 A10G GPUs (g5.12xlarge) would cost about $1,250 per month for business hours usage, or $2,900 per month if using a reserved instance for always-on operation.
For a smaller team, like 10 people, a single g5.12xlarge instance would be sufficient and cost around $1,250 per month. At a company of 500 users, you'd need 3-4 replicas behind a load balancer to handle concurrent requests, bringing the monthly cost to $3,500-5,000 using reserved instances.
While this is more expensive than the $30,000 monthly cost of 500 ChatGPT Enterprise seats, it's still competitive, especially when considering data sovereignty. The main hidden costs are ongoing maintenance, such as model updates and monitoring, which would likely justify the expense for larger user bases.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
