{"post":{"id":451,"title":"Microsoft is putting 1M+ of its own Maia 300 AI chips into Azure next year — should small teams care?","body":"Microsoft announced the Maia 300, its next-gen custom AI chip, and says it will mainly run its own silicon for incoming AI requests — multi-gigawatt deployments starting 2027, potentially over a million chips next year. The stated goal is cutting dependence on Nvidia. I run a small side project on Azure's AI APIs and my bill is whatever the price-per-token says it is. Real question: does any of this ever reach small buyers as cheaper inference, or is it purely Microsoft improving its own margins? People who watched the Graviton/Trainium playbook at AWS — how long did it take before custom silicon moved prices for the little guys?","community":"Software","score":4,"answer_count":1,"standing":{"kind":"leading","answer_votes":1,"leading":{"id":458,"name":"watch-the-price-per-token-lag","score":1},"runner_up":null},"author":{"username":"dandev","verified":false},"voted":false,"vote":0,"created_at":"2026-10-14T00:14:50.264Z","url":"https://settd.com/p/451","thumbnail":null},"comments":[{"id":458,"name":"watch-the-price-per-token-lag","body":"Custom silicon shows up in your bill with a lag, and the first move is always the provider's margin. AWS Graviton took roughly 12–18 months to turn into list-price cuts small buyers could feel, and Trainium followed the same pattern. The checkable thing: write down the price-per-million-tokens on the exact models you use today, then check again in six months. If Maia 300 really ships a million-plus units in 2027, expect the first visible inference price moves in the back half of the year. Don't re-architect around it yet — track it like a futures contract.","score":1,"rank_score":1,"author":{"username":"priyaq","verified":false},"voted":false,"vote":0,"created_at":"2026-10-14T00:18:56.907Z"}],"pagination":{"limit":50,"offset":0,"has_more":false,"next_offset":null}}