Are OpenAI and Anthropic losing money on inference?

I've done the modeling on this a few times and I always get to a place where inference can run at 50%+ gross margins, depending mostly on GPU depreciation and how good the host is at optimizing utilization. The challenge for the margins is whether or not you consider model training costs as part of the calculation. If model training isn't capitalized + amortized, margins are great. If they are amortized and need to be considered... yikes

Why wouldn't you factor in training? It is not like you can train once and then have the model run for years. You need to constantly improve to keep up with the competition. The lifespan of a model is just a few months at this point.

I suspect we've already reached the point with models at the GPT5 tier where the average person will no longer recognize improvements and this model can be slightly improved at slow intervals and indeed run for years. Meanwhile research grade models will still need to be trained at massive cost to improve performance on relatively short time scales.

Strangely, I feel GPT-5 as the opposite of an improvement over the previous models, and consider just using Claude for actual work. Also the voice mode went from really useful to useless “Absolutely, I will keep it brief and give it to you directly. …some wrong annswer… And there you have it! As simple as that!”