My personal experience is best with GPT but it could be the specific kind of work I use it for which is heavy on maths and cpp (and some LISP).

Would you install someone else's binary blob to give it those much permissions and your API keys? The measures required to run that somewhat trustless complicate things a lot.

Granted the experience can be worse, esp. if you're using it very hands-off and not like a junior assistant who's extremely fast but doesn't know what he's doing at the architecture and strategy level. But even for that I'm relatively confident the Chinese will be competitive pretty soon, and they won't be too expensive. And we know this because we can see their current models and we know what it takes to run them.

Currently my Strix Halo computer that costed me under £3k can do a lot of LLM stuff that is perfectly useful. In some ways, it's better than "cloud" models, I have models that essentially don't say "no" and I have relatively predictable setups. If you want to get fancy, you can right now rent compute to run models that are extremely capable like the latest ones from Kimi, GLM, Qwen, Minimax at full size from providers that are not operating at a loss and it won't be too expensive. You can pool resources to do the same locally. You can do stuff that cloud providers are unlikely to market, like distillation and abliteration to serve your specific needs.

I'm very optimistic about open weights models just the way they are right now.

But I agree with you that OpenAI will likely play similar games to Anthropic and it could be soon.

it has been reported that it behaves very differently depending on those factors, presumably because people are placed in best-effort buckets, who knows

Meanwhile this mythical beast wasn't able to prevent the Bun vulnerability that exposed their code, let alone precluding the need to acquire that IP in the first place for presumably hundreds of millions of $$$, instead of coding a better replacement or a solution of its own.

What is real and measurable is that subscription plan users are getting a much degraded service for the same money through both open and hidden policies, while Anthropic moves compute to serve off-the-counter customers. The same people who come with the most obvious and brazen lies to dismiss the clear degradation of their service also come with this "security" justification for a move that looks just like good old market segmentation which would perfectly fit the strong symptoms that they cannot afford to offer tokens at a competitive price in this market.

However we cannot observe these things directly and it could be simply that OpenAI are willing to burn cash harder for now.

they're looking to IPO in 2028 vs 2030 for OpenAI, who have raised more than double the funds

so they're willing to play fast and loose with the terms and conditions of existing customers trying to make it happen

those pockets must be drying up really fast

I look at the output of Kimi and the costs of running inference on it that i can replicate, and it isn't that bad, although admittedly i don't have to worry anywhere near as much about scaling it and about having to dedicate large amounts of compute to research and distillation on the back end. It's true that it's perhaps a step behind SotA vs January's Opus or current Codex, depending on what you do. But not by a lot. In fact it's leaps and bounds superior to the current subscription API experience. Together with GLM, Qwen and Minimax they are an amazing backstop just the way they are right now.

With all the layers of obfuscation it's hard to even know roughly how many i/o Opus tokens do Claude subscriptions pay for. They'll give you some flippant arguments like "people were not looking at thinking so we're not showing you anymore" with a straight face. However podcasts still insist Anthropic are "winning the AI war" (??) it really makes me wonder because in no metric I can see them as providing neither best value nor best quality, and let's not get started about consumer experience.

My intuition is that things must be really bad so they're willing to pull the kind of moves they're pulling right now. They're speedrunning people into understanding how important it is to be able to run your own generative AI infrastructure for reliability, thus becoming a very fancy but trustless throwaway solution factory.

I wonder if OpenAI will turn the screws similarly if/when their pockets start to dry up at a certain pace.

I don't give them large tasks that i wouldn't be able to work on myself, so that's maybe part of it.

*typo

China is a deeper decline than Japan too, which will make their geopolitics volatile