For a solo dev sure.. but isn't there a huge privacy difference between Anthropic and DeepSeek APIs as well? I assumed part of the cost for Anthropic was essentially a privacy premium.. (plus they offer B2B).
DeepSeek V4 – almost on the frontier
281–290 of 420 posts
Re: DeepSeek V4 – almost on the frontier
#282Tokens are cheap. LLMs are fast. Pre-processing and post processing are the real bottlenecks. I know you are going to say that why not Use LLMs for that. Complexity in an end-to-end workflow is a zero-sum game. If you throw more of that workflow to LLM, more complexity comes back to you, to those steps that you need to do on your own. If you keep only 10% of work for yourself, it's going to be 10 times more complex and rapid than what you usually do.
Re: DeepSeek V4 – almost on the frontier
#283Earlier quoted context omitted.
Well, I'm using all the top models extensively on the very same codebase, my new compiler. I use deepseek for it's cheap API costs, when kimi, claude and codex are in their overbudget phase. I asked deepseek V4 Pro for an estimate of a new arm64 port. It said 4 weeks, I said, ok, do it. (I knew ncc was there, and tinycc was also known to the AI's). So it took it half an hour to produce a working arm64 port. First for…
Your method of combining models to strengthen the implementation reminds me of how we form stronger alloys by combining metals!
it also sounds like a lot to manage, do you have some sort of agentic framework that's treating all of these llm's you have access to as sort of inputs that it optimizes?
Re: DeepSeek V4 – almost on the frontier
#284For a solo dev sure.. but isn't there a huge privacy difference between Anthropic and DeepSeek APIs as well? I assumed part of the cost for Anthropic was essentially a privacy premium.. (plus they offer B2B).
Presumably you can run open model in your own infra
Re: DeepSeek V4 – almost on the frontier
#285Earlier quoted context omitted.
There actually is a very important distinction between "would if they could" and "they can and do", though.
Uhh right, but describing that as "dystopian" is frankly hysterical. It's an obvious corollary of good things (like product liability). Virtually everyone I've heard complain about these safety rails was up to antisocial (at best) stuff. I've never heard a sympathetic use-case. It's objectively good that companies can be held responsible for misuse of their products and that they are therefore incentivized to mitigat…
Yes, my safety cap policy is definitely anti-social.
Re: DeepSeek V4 – almost on the frontier
#286Earlier quoted context omitted.
Uhh right, but describing that as "dystopian" is frankly hysterical. It's an obvious corollary of good things (like product liability). Virtually everyone I've heard complain about these safety rails was up to antisocial (at best) stuff. I've never heard a sympathetic use-case. It's objectively good that companies can be held responsible for misuse of their products and that they are therefore incentivized to mitigat…
Yes, my safety cap policy is definitely anti-social.
"These safety rails" was referring to LLMs, which have far more nuanced and capable safety rails than chemical caps do, and accordingly also have much more assertive ways to enforce them.
Re: DeepSeek V4 – almost on the frontier
#287Earlier quoted context omitted.
At least that’s what they’re telling you. It’s a ”trust me bro” scenario. I’d rather use the phone home version (deepseeks own endpoint). The benefit is that I’m fairly certain that they actually host the model I’m paying for.
If you're not Chinese, and you start a company outside of China, and your whole pitch is "We run open weights and we have nothing to do with China", 1) why would send data to China?? 2) why would you risk your business to do a thing that makes no sense?
Well, the context was running the models via open router, not hosting 800B> models yourself. Of course, if given the option I believe most people would pick ”don’t share sensitive data”.
What I’m trying to say is that EVERYONE uses your data, even the sensitive type. So you might aswell use an endpoint that does what it says and treat EVERY endpoint whether that’s OpenAI or anthropic as if it’s collecting all of your data.
Re: DeepSeek V4 – almost on the frontier
#288Earlier quoted context omitted.
At least that’s what they’re telling you. It’s a ”trust me bro” scenario. I’d rather use the phone home version (deepseeks own endpoint). The benefit is that I’m fairly certain that they actually host the model I’m paying for.
Some providers are based in the US or EU and would face legal repercussions for lying about what they do with your data. It's a bit more than "trust me bro". Off the top of my head, you can use Fireworks, for example, which is based in California and would face the same consequences for lying about their data policy as OpenAI or Anthropic would.
Meta is based in the US, yet they torrented TERABYTES worth of books to feed their AI.
I’m not trying to be negative here, but your point is invalidated by that particular event in itself.
Re: DeepSeek V4 – almost on the frontier
#289Naive Question: is DeepSeek V4 actually cheaper to run? Or is it cheaper because of other reasons? For example Anthropic running at a higher margin or DeepSeek at a larger loss?
I believe that DeepSeek-V4-Pro API at promotional pricing (https://api-docs.deepseek.com/quick_start/pricing) could run at almost exactly 200 % profit.
If you take DeepSeek's numbers for DeepSeek-V3 (https://github.com/deepseek-ai/open-infra-index/blob/main/20...) and plug in ~3333 tps/GPU for DeepSeek-V4-Pro (https://developer.nvidia.com/blog/build-with-deepseek-v4-usi...) and a price of $7/hr per B300 GPU, the profit comes out as 202%.
The rumor is that Anthropic's Opus models have ~100B active parameters, which is twice as much as DeepSeek-V4-Pro, so inference is at least twice as expensive. Since the API pricing is almost 30 times that of DeepSeek, Anthropic's margins are likely very healthy. But they have to be, since Anthropic has to offset the model training costs, while DeepSeek is backed by High-Flyer Quant. DeepSeek might still be profitable anyway, but without knowing how much they spent on training and wages, we can't really tell.
Re: DeepSeek V4 – almost on the frontier
#290Earlier quoted context omitted.
We need that lawsuit to happen already so we can establish precedent. The person in the driver's seat of the Tesla should be at fault. The engineer using the llm should be at fault. The person behind the gun not the manufacturer should be at fault.
> The person in the driver's seat of the Tesla should be at fault. I don't think this is a good analogy. For Tesla right now it might fly. However, when their software gets to waymo level of autonomy, I would expect liability to shift to the manufacturer. If anything, I think that would be the true proof of a company trusting their software to allow for autonomous driving
> However, when their software gets to waymo level of autonomy
Luckily that won’t happen.