Yes, that's exactly why I avoid OpenAI and Anthropic products.
Besides the (quite true) joke, if sending data to DeepSeek is a concern the good thing is that the models are open weight, you can self host them or use third party providers.
You can theoretically self-host. DeepSeek is big. DS4 (the 2-bit quantization of DeepSeek Flash) runs on my Strix Halo with 128GB, but it's slow as hell. Completely unusable for interactive work. But, I guess a company that cared about data privacy and wanted a Good Enough local model could spend $100,000 or more on hardware to run it properly.
The DS4 author has demoed upcoming work on Strix Halo that makes it roughly competitive with the Apple Silicon equivalent (i.e. Pro models with similar memory bandwidth figures, not Max or Ultra). Maybe even a bit faster for prefill, and with further potential for running small batches in parallel (since the GPU clearly has some amount of compute headroom during decode).
As far as I can tell you'll have a context limit of about 64k, which is also prohibitive for serious work. (My benchmark maxes out at 90k in context when running, so I'm giving the self-hosted models 128k to leave plenty of wiggle room.)
But, still, it's cool that the work is happening. For some classes of problem it might be an option, and when the 192GB Strix Halo comes out, DS4 will probably become a real contender for self-hosting champ, as that leaves enough memory for a big context.
> As far as I can tell you'll have a context limit of about 64k
Source? The author has demoed a 100k ctx already, and I can't think of a reason why more wouldn't be supported. RAM is a bit tight but that only matters with really long contexts on DeepSeek V4, and proper support for SSD streaming would address this anyway.
OK, I just tried it with the new mainline ROCm and MTP support, and it is faster, but still uncomfortably slow for interactive coding agent use. It does about 14-15 t/s, which is faster than the 10-11 t/s I was seeing before, but still a crawl. I set it loose on a small 300-line Perl file, and it's still chewing several minutes later.
So, it's super cool that such a solid model can run locally and it's probably useful for batched work overnight. But, I'm not going to sit around twiddling my thumbs while working. I think I can write code by hand faster than this. I'll gladly pay for a cloud model so I don't have to wait (especially since DeepSeek models are so cheap).
No source, just back of the envelope math. 100k seems optimistic, but I guess I'll try it and see. That would be usable for at least a few use cases, including the security scanning work I'm focused on at the moment (at least, so far, the peak token usage has been 90k, which would make 100k tight but probably fine).
Unless you meant being concerned about hosted AI in general, not specifically DeepSeek. In which case yeah that's a huge concern to me but I can't reasonably afford a half million dollar appliance to self host a large model at reasonable performance and don't have anywhere to put one even if I could.
These days I'm also worried about US companies having my data. I hate that we're at that point, but with Trump talking about taking an ownership stake in AI companies, and tech companies, including the leading AI companies, lining up to participate in the war crime of the day, I don't have a lot of faith my data is any safer with US companies than those in China.
Though, I added Mistral's latest model to the mix in the hope that some European model could be a contender, but it failed completely. I don't know if it hit safety guardrails or is just not competent at security work, but it scored 0/9. No errors, it returned the empty JSON set it was supposed to return if it didn't find anything. But, there were plenty of real bugs to find, and some very small self-hosted models found at least some of them.
I think it is a bit naive to assume that companies that have built their moats on violating copyright, scraping and ddosing all of the internet, and distilling each other's models will not leverage our data if they can have financial benefits out of it.
I don't think that the country matters, whoever you send data to among these AI labs you are at security risk and data risk.
I hope that someday there are AI companies for whom ethical behavior is a selling point. We're certainly not there for the current leaders, though vibes vary a little bit between them. Some seem scarier than others.
Besides the (quite true) joke, if sending data to DeepSeek is a concern the good thing is that the models are open weight, you can self host them or use third party providers.