Well things may change soon. I've been testing Coding fulltime with Deepseek Flash this week to evaluate an eventual shift for the whole company away from anthropic. It has been quite positive and I can't wait to try pro tomorrow. If our data has to be used by either US or China, we might as well go the cheaper and unwalled garden. If only it supported image input ...

Hacker News is very Bay Area/US tech centric where spending a few hundred a month on AI is just pocket change. The weaker AI models with more questionable data retention policies are popular in developing countries. I think the new Facebook muse model will be similarly popular.

Well, one reason is that we always have to work with the quirks of each model. So, a know model is often preferred over a new/unknown one because we have to be vigilant again. (Negative) surprises are mentally exhausting in the long run. IMO, you can work much better when you know the model.

In an enterprise setting Chinese models are often discouraged due to political risk. They don't want to need to remove a model that's deeply embedded in their stack. And it's entirely feasible that the US gov bans federal contractors from using them in the next 6 months for example, or that EU AI safety rules effectively ban them too.

There are EU/US providers offering Deepseek/Qwen/Kimi/etc.-as-a-Service. With zero ties of their infrastructure to China.

Fully compatible with the well known Antrophic API.

You only have to replace the URL and your key.

Based on what the political climate looks like nowadays it's entirely possible the US bans federal contractors from associating with any company that uses the models themselves, regardless of data provenance or where they are hosted. Or they create AI safety rules that make it impossible to release open source models (for example, making it so that closed-source models can be evaluated with a harness but open-source models need to pass the benchmark with the weights alone, which isn't really possible). Or they just declare Chinese models a security risk like TikTok (claiming that the model would be trained to respect Chinese interests).

It may not be likely but it's definitely possible enough to be something people worry about.

Yeah, but ask them about Tiananmen square.

Then run the DeepSeek or Qwen model on AWS GovCloud, etc., and you won't have any risk of exposure to "China".

I'm not even sure what "EU AI safety rules" are. Can't people in the EU just use whatever they want?

Running on AWS GovCloud isn't necessarily an option, some places prohibit running Chinese origin models even locally.

I suspect if you follow dev groups in developing countries people are much more focused on token/ price efficiency.

For funded startups it mostly just doesn’t matter a ton unless you are passing on inference in your product at scale

There's just no place for models that are neither SoTA nor truly crazy cheap in today's public mental health climate.

If it's 500x cheaper than US models for similar ballpark performance just because it's hosted in China, sure whatever. If it's name brand like Anthropic/OpenAI/Google, that's kinda fine too.

If it's neither, like merely 50% cheaper than latest OpenAI whatever, however massive loss that pricing may be incurring to its provider, it wpuld be considered not worth any attention.

I keep using Claude and Codex simply because the subscription rates are SO MUCH cheaper than per-token rates, even with the cheaper models

A lot of it/infrastructure departments aren't aware that you can use Asian models hosted within the US or even EU.

Most of my model usage comes from my work’s model selection (which is now down to just Claude models)

I’ll try out the latest models, but mainly stick with Claude only because I’m most used to its quirks and how to work around them. I imagine this is part of these hyperscalers playbook.

I will say though, I miss Sol model at work. It with Codex was amazing at first-shot understanding. Claude i need to scope out where to look otherwise a large portion of my token budget is eaten up