But they make up for it by shipping it late.

It's also got vision and audio. So, the better comparison is any of the other large Chinese open models that are better and cheaper than Gemini Flash.

Google's models are always very well spoken and much more pleasant to talk to. And I've used the open weight models a lot, too.

It's also about 15x faster.

It's roughly equal on price and intelligence as GLM 5.2 while being ~8x faster.

It’s multimodal though.

It'd be interesting to know how much the Intelligence as a Service angle serves as a value-add in the minds of Google's executives.

You can get decent open-weight models now. That's not difficult. The difficulty is 1) running them and 2) compliance.

My company runs Claude on GCP's Vertex AI solution. We're in the US healthcare IT space, so the models need to be from somewhere that American healthcare agencies and companies have traditionally been okay with sourcing code from - which means the US, Canada, and maybe Europe. The stuff that handles PHI/PII must be in the US. The expense of hosting is more of a PITA than most customers want to go through this early in the technology's lifecycle, and intelligence gains are simply a matter of degree for most business tasks.

In theory, we could find some open-weight model (likely from China) for our development agentic work and host it anywhere you can host AI models. We don't, though, and I think Google, OpenAI/Microsoft, and Anthropic see that as the core of their business.

Is that statement based on token price? More and more it seems that $/token hides as much as it reveals. Token efficiency, tokenizer differences, etc. I'm not saying that you are wrong, I am just saying it is becoming a bit more difficult making statements like this without a bit more research.