161–170 of 201 posts
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They did release the weights and there are many providers https://openrouter.ai/deepseek/deepseek-v4-flash-0731#provid... Deepseek's official API has a pretty bad privacy policy so I would assume businesses avoid them in any event
it says they actively train on your data
Which is a real bummer because it’s otherwise solid with excellent caching.
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Yeah it feels like a very different model. I don’t try to fill up Apple/Google cloud drives to 1TB because then I’d have to clean up when I need space. I don’t bother trying to maximize my Audible subscription because there’s only so much I can listen to in a day. Even with my other AI subs that have monthly credits that don’t carry over, I just don’t have the interest or time to burn the credits. But my Claude Max s…
And there's the rub. Firing off the task produces the dopamine hit, signaling you're doing something, but if you never read the output...are you really doing anything at all?
I am however going to fire off a half assed prompt when the marginal cost is zero, even if I don’t use it (which is par for the course, I probably throw out two thirds of anything the AI writes anyway be it code or prose).
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Yes. I focus on pricing software and I’m a bit baffled why frontier models are pushing tokens. It’s a race to the bottom, and the bottom is unlimited use for a flat monthly rate. Granular pricing (tokens, minutes, etc) is pretty anti-customer generates less revenue than customer value-based subscriptions (why SaaS is such a good business model)
I've always been curious about who works on software pricing. Do you guys hire actuaries for this type of work?
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Yes. I focus on pricing software and I’m a bit baffled why frontier models are pushing tokens. It’s a race to the bottom, and the bottom is unlimited use for a flat monthly rate. Granular pricing (tokens, minutes, etc) is pretty anti-customer generates less revenue than customer value-based subscriptions (why SaaS is such a good business model)
I've always been curious about who works on software pricing. Do you guys hire actuaries for this type of work?
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It's worth keeping in mind the model doesn't keep a running memory. Each time its instantiated, it begins from its release state - so from its perspective (if it had one) the current task would be the first stop after posttraining. Perhaps the only stop. Though of course you're talking about data centers, and romanticizing them rather than the AI itself.
Why do they do it this way? Because dogfooding is harmful to the model? Is this implying there's no benefit in having the model train on itself?
There are various theories around model collapse when you train on too much AI generated data (that's not for distillation).
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200% increase over practically free is still practically free
It mostly hurts people in countries with weak purchasing power. DS was the main game in down for them. Personally, I don't think we've seen the total end of dirt cheap LLMs, it's just a frontier lab doesn't want to be in business of serving half the world.
As someone from just such a country, DeepSeek 0731 was the first time I seriously started using an LLM for coding. All previous attempts were useless or ridiculously expensive.
Can't say the old prices felt "free", but it was affordable if you're careful with your cache hit rate.
The new pricing probably pushed it into the unaffordable territory for tasks where you can do without it. Probably will try opencode go if they don't also follow suite, or will have to go back to wetware.
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They did release the weights and there are many providers https://openrouter.ai/deepseek/deepseek-v4-flash-0731#provid... Deepseek's official API has a pretty bad privacy policy so I would assume businesses avoid them in any event
it says they actively train on your data
Interesting to see that peak hours are work hours in China, night in the US and Europe, and also morning in Europe. So Deepseek's customers are mostly domestic.
Yeah I saw complaints about this under their twitter announcement, that they're giving discounts to the rich foreign customers and screwing their own people.
Ever since I started using flash, it has slowly crept up to be my default for everything. It is at the good enough state for a fraction of everything else that's out there.
Have you compared it to Luna? I was using Flash for small tasks before, then switched to Luna when they dropped the price. The benchmarks show that Luna is significantly faster, but I think those are very complex tasks for which you'd probably want a bigger model anyway. (e.g. Sol is much faster than Luna at the same tasks.) So I'm wondering if there's any difference for smaller tasks, or if they're basically matched…