Source: I worked there
Culture is overrated. Money talks.
They did things far more complicated from an engineering perspective. I am far more impressed by what they accomplished along TSMC with Apple Silicon than by what AI labs do.
Google invented the transformer architecture, the backbone of modern LLMs.
Apple has no control over the most important change to tech. They have control to Google.
No one can outpace them in improving the SOTA, everyone can catch up to them. Why are open-weight models perpetually 6 months behind the SOTA? Given enough data harvested from SOTA models you can eventually distill them.
The biggest differentiator when training better models are not some new fancy architectural improvements (even the current SOTA transformer architectures are very similar to e.g. the ancient GPT-2), but high quality training data. And if your shiny new SOTA model is hooked into a publicly available API, guess what - you've just exposed a training data generator for everyone to use. (That's one of the reasons why SOTA labs hide their reasoning chains, even though those are genuinely useful for users - they don't want others to distill their models.)
Frankly, a lot of times I prefer using GLM 4.6 running on Cerebras Inference, than having to deal with the performance hiccups from Claude. For most practical purposes, I've seen no big penalty in using it compared to Opus 4.5, even the biggest qwen-coder models are pretty much competitive.
Between me and the company I work for, I spend some serious money with AI. I use it extensively in my main job, on two side projects that I have paying customers for, and for graduate school work. I can tell you that there quite a few more SOTA models around than what the benchmarks tell you.
Yes I forgot xAI. So 4 left. I’m betting that there will be one or two dominant ones in next 10 years. Apple won’t be one of them.
