According to @StockMarketNerd, mega-cap platforms are pursuing in-house AI chips because paying a GPU vendor with roughly a 66% EBIT margin makes it hard to compete on cost, impacting overall compute efficiency per dollar of CapEx; source: @StockMarketNerd on X, Nov 25, 2025. The post argues that even if internal accelerators are inferior, they can be good enough at a fraction of the price, enabling more compute and utility for the same capital; source: @StockMarketNerd on X, Nov 25, 2025. For traders, this framework highlights potential medium-term pressure on NVDA pricing power and margin sustainability if large customers substitute with internal hardware; source: @StockMarketNerd on X, Nov 25, 2025. It also flags a relative advantage for firms that successfully deploy in-house accelerators, which could shift AI capex share-of-wallet toward internal solutions; source: @StockMarketNerd on X, Nov 25, 2025. The post does not reference cryptocurrencies or tokens, and its focus is AI hardware economics and cost efficiency; source: @StockMarketNerd on X, Nov 25, 2025.