Comment by nullbio
20 hours ago
Where are the model stats? Is this open-weights? If not, why would I use this over DeepSeek Flash 4.1?
I think these competing labs need to realize that no one wants another closed-weight model provider... We aren't even happy with the two we have right now, and their days are entirely numbered. If DeepSeek 4.1 flash is really as good as it's benching, we're probably a month away from 1/3rd of users moving off the closed-weight models in favor of something they have more control over (or is cheaper).
The big labs love to release their new model and quantize after the first week. You don't have that problem using dirt cheap API rates on OpenRouter. DS 4.1 flash is also faster than fast mode Astra. OAI's subscription rates are good value, but now these new open-weight models are nearly as cheap on API usage rates. I honestly can't wait for the day we're not beholden to the two big labs anymore. No wonder there's so much fear pumping happening at the moment from Anthropic and their funded NGOs.
This really just exists so cognition can stop spending API tokens with Anthropic or OpenAI.
Basically any successful AI based service will do this because at scale the frontier models are expensive and you’ll have enough data to fine tune your own.
Same reason Harvey is doing models now and basically every other provider
Couldn't they just grab and run an open weight model to save on API tokens?
You get better performance if you also finetune it for your task
> If DeepSeek 4.1 flash is really as good as it's benching, we're probably a month away from 1/3rd of users moving off the closed-weight models in favor of something they have more control over (or is cheaper).
Only in the world where the incumbents don't react. Eg if they saw lots of users moving away, they'd drop prices or do something else.
1M cached tokens on deepseek is $0.006, the big labs can't sell anywhere close to this, they have funders expecting returns and huge overhead.
btw I've had a ton of fun with the new deepseek today, I was waiting for my OpenAI 5h limit reset and decided to give it some problems for fun, got pretty great results. Tried some harder problems and still got great results. I don't expect it to be Sol class or anything but I really didn't expect it to be anywhere near this good so we'll see where it ends up. And it's really fun throwing crazy amount of tokens at the wall for ~free instead of watching the subscription limits tick closer while your agents churn away.
> 1M cached tokens on deepseek is $0.006, the big labs can't sell anywhere close to this, they have funders expecting returns and huge overhead.
Losing most of your customers tends to sharpen the mind a bit. They could eg stop pushing out the absolute frontier for a while and focus on making what they have run cheaper. Or they go and do more lobbying against China. Or a million other little things that take more than 30 seconds to come up with when writing a HN comment, but less than a week for someone who's smart and paid to do this for a living.
I did a lot of that kind of work with the older version of DeepSeek before they upped the prices.
For example, it was quite good to get a decent Sashiko review. Sashiko is a Linux kernel review agent with interchangeable LLM driver. It's very good, but it eats tokens like crazy.
That's 1/3 of GPT 5.6 Luna. It seems rather close to me.
But great that we have a new leader in performance/price in that segment.
Yep. 4.1 Flash is good enough for most routine coding things, but it also makes up for a lot of weakness by being so fast (and cheap of course).
I'm willing to tolerate babysitting things a lot more if I know I'll get almost instant results.
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OpenAI just paused new subscriptions to their $200 plan. They are in a rock and a hard place. Obviously the Astras and Fables of the world are exponentially more expensive, but for...less than exponential returns. The question is whether they can leverage the marginal advantage into something that justifies the diminishing returns before the bottom catches up to them.
On the one hand you, if you bought a lot of compute a couple years ago (perceived demand, perceived shortage) you are in a good spot temporarily. But the counter to that is that everyone else is becoming more compute efficient so maybe that advantage isn't what people thought it would be. I can almost, almost run DS4.1 Flash at home. 4 sparks can do it at 200+ tokens per second. I have two Sparks, so I am not in the club. Neither is your average laptop owner or gamer either. But your average HN software engineer can probably easily swing 2 sparks.
> But the counter to that is that everyone else is becoming more compute efficient so maybe that advantage isn't what people thought it would be.
I'm not sure? If we have techniques to use the hardware even better, that will make the hardware even more valuable, won't it?
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I could buy four of them for ~20k.
That's like four years of ChatGPT + Claude subscription.
Eight years if only ChatGPT, or sixteen years of the Pro 5x subscription.
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> we're probably a month away from 1/3rd of users moving off the closed-weight models in favor of something they have more control over (or is cheaper).
DS 4 Flash requires large amounts of memory to run at reasonable quants (I think a system with 160 GB or so). DS 4.1 Flash is even larger, I think around 250 GB.
Any DS version is dumb when compared (in realworld tasks) to Astra/Opus 5, which means, one would spend thousands of dollars, and still need to rely on cloud services to do jobs that are non trivial.