The hidden cost of self-hosting enterprise AI
By Chitral Patil
As generative AI moves into production, enterprises face an important infrastructure decision: consume models through commercial APIs, deploy open-weight models on dedicated GPUs, or combine both approaches?
The comparison is often reduced to simple arithmetic. Divide the hourly cost of a GPU by a model’s maximum token throughput and compare the result with an API provider’s per-token price. By this method, self-hosting frequently appears dramatically cheaper.
But a provisioned GPU does not automatically operate at benchmark throughput.
Why enterprises self-host
Cost is not the only reason to choose dedicated infrastructure. Some workloads require tighter control over where data is stored and processed, who can access it, how models are configured, and how systems are audited. Privacy, data sovereignty, customisation and operational control can justify self-hosting even when its raw per-token cost is not the lowest.
These benefits are real, but they should not obscure the economics. The...
Copyright of this story solely belongs to expresscomputer.in. To see the full text click HERE
