Thoughts on LLM inference cost vs. market expectation for Q3/Q4

Been following the AI space pretty closely, particularly the race to optimize LLM inference. We've seen some pretty impressive gains in efficiency lately, but the market's still pricing in, what I see as, a fairly aggressive timeline for widespread, dirt-cheap, high-quality inference becoming the norm.

My take is that while the trend is undeniably towards lower costs, the rate of that cost reduction for truly powerful, complex models (think beyond basic chatbots) will likely hit a slight plateau in late Q3 into Q4 before another significant step-change. We're seeing diminishing returns on some of the current architectural tweaks, and the next big leap likely involves more fundamental hardware or algorithmic breakthroughs that take time to scale. I'd put the odds at about 65% that we see some key players in the AI infrastructure or cloud space adjust their projected Q3/Q4 inference cost reductions slightly downwards, or at least deliver improvements at the lower end of their guided ranges. This isn't to say it won't get cheaper, but the exponential curve might flatten out a bit sooner than some of the more optimistic analysts are currently forecasting. This could have a subtle but noticeable impact on valuations for companies whose entire bull case is predicated on practically free, instant, top-tier AI services within the next six months.