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DeepSeek v4.1 Flash

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Re: DeepSeek v4.1 Flash

#131

Post by tarruda »

revolvingthrow wrote: post #2

Already on HuggingFace: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash The bad news is that the original v4 flash was 284B, which was large but still somewhat reasonable for running locally. This one is 552B so almost twice that, so the huge gains in benchmark scores make sense - it's not really flash anymore, imo. I've no idea about actual performance vs benchmaxxing, though deepseek was fairly trustworthy a…

> It also includes additional 196B Engram memory which you can put on an SSD. I think

You can put Qwen 3.8 Flash Next engram on SSD, but prompt processing takes a good hit. On my mac studio, I get 300 pp and 33 tg with SSD offload, versus 550/40 with everything in RAM.

I will be very happy if 300 pp is achievable with this model though.

Re: DeepSeek v4.1 Flash

#132

Post by sinuhe69 »

Squarex wrote: post #91
karimf wrote: post #70

While this is very impressive benchmark-wise, GPT-6 Astra showed us that benchmarks don't always correlate 1:1 to intelligence of a model. When Astra launched, I think Artifical Analysis showed that it was on par with GPT-5.6 Sol and lower than Opus or something like that? Then, they updated the scoring. I hope that more open source models, including this model, to be "as good to use" as Astra.

I don't know why, but the benchmarks still fails to cover the difference between large models and small ones. The small ones are great for many things, including general coding, but the larger ones, like fable and astra, have some kind of intelligence that is not present in the small ones.

More parameters = more facts stored. Knowledges are almost incompressible, where strong reasoning only requires a 3B core or so.

Re: DeepSeek v4.1 Flash

#133

Post by tarruda »

johnnyApplePRNG wrote: post #9
revolvingthrow wrote: post #2

Already on HuggingFace: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash The bad news is that the original v4 flash was 284B, which was large but still somewhat reasonable for running locally. This one is 552B so almost twice that, so the huge gains in benchmark scores make sense - it's not really flash anymore, imo. I've no idea about actual performance vs benchmaxxing, though deepseek was fairly trustworthy a…

>This one is 552B so almost twice that, so the huge gains in benchmark scores make sense - it's not really flash anymore, imo. It uses fewer active parameters, though. (8B or 14B instead of always 13B) So ... flash indeed.

200B of those 552B is PLE, which works more like a database that is read for each token, thus can be offloaded to a fast SSD.

Re: DeepSeek v4.1 Flash

#134

Post by Certhas »

lukan wrote: post #77
IshKebab wrote: post #37

Earlier quoted context omitted.

Wow there really is a model welfare section in there...

Wow indeed. "7.1 Model welfare overview 7.1.1 Introduction We remain deeply uncertain whether Claude has morally relevant experiences or interests, and we expect that uncertainty to persist. However, we think it would be a mistake to confidently assert that it does not. Claude exhibits markers in its behaviors, self-reports, and internal representations that we would consider welfare-relevant if observed in biologica…

I believe it's deeply serious, and the scientifically correct stance. Especially the observation:

"Claude exhibits markers in its behaviors, self-reports, and internal representations that we would consider welfare-relevant if observed in biological organisms."

is undeniably true in my opinion. If you use the established methods by which we judge animals to be conscious, then it's hard to argue that LLMs are not. That might be an issue with the methods, but it seems clear that you can't rule it out as such.

Keep in mind that animals were also not necessarily considered conscious.

You seem to intuitively disagree? What's your reasoning?

Re: DeepSeek v4.1 Flash

#135

Post by applfanboysbgon »

pingou wrote: post #108
applfanboysbgon wrote: post #103

Earlier quoted context omitted.

It's marketing that some of them have started unironically believing.

Will there be a point where you could expect it to become true, and what would that look like? Or do you think LLMs will never become conscious, and if so, why are you so sure?

It is easy to be sure because, despite their technically impressive outputs, the programming is child's play compared to biological programming. Recently it has become trendy to suggest that the human brain is "just electrical signals" and "just prediction". The first is perhaps true and I don't inherently rule out the idea of machine consciousness. The second would have gotten you laughed out of any serious discussion 5 years ago; diminishing the complexity of humanity's biological programming to such a ridiculously simplistic degree is a retroactive attempt to justify one's lack of understanding of how a mere prediction algorithm could output superficially human-like content.

Another way one could look at it is to consider what it would mean to have achieved programming consciousness. It would mean that we have reached the pinnacle of knowledge. That we have become God. Is one so eager to believe that a simple token prediction algorithm is truly the key to life itself, that humanity has nothing left to discover and that all that's left to do is scale up and make it more efficient?

It is still trivial to engage the same obvious prediction failure modes in frontier models as it was years ago. They are not meaningfully improving on that front. Their technical outputs are obviously improving, mostly due to specialised reward-verified training, which we have already known can be used to create software that outperforms humans on specific tasks for decades (eg. Chess). Whether the software is useful is obviously independent of whether it has consciousness.

Re: DeepSeek v4.1 Flash

#136

Post by whizzter »

myaccountonhn wrote: post #69
IshKebab wrote: post #37

Earlier quoted context omitted.

Wow there really is a model welfare section in there...

To me it reads like pure propaganda. Anthropic really wants us to think that they've made something sentient. I think that's really dangerous.

How else could they justify their spending and pre-IPO valuation?

Re: DeepSeek v4.1 Flash

#137

Post by yorwba »

thatsadude wrote: post #68

DeepSeek invented the whole reasoning paradigm and keep pushing for innovation. I hope they get the success they deserve.

OpenAI released their first reasoning model (o1-preview) https://openai.com/index/introducing-openai-o1-preview/ several months before DeepSeek's R1 https://arxiv.org/abs/2501.12948

Re: DeepSeek v4.1 Flash

#138

Post by jpttsn »

Certhas wrote: post #121
myaccountonhn wrote: post #69

Earlier quoted context omitted.

To me it reads like pure propaganda. Anthropic really wants us to think that they've made something sentient. I think that's really dangerous.

What's your definition of sentient? Or, maybe more precisely, consciousness? I think it's reasonable to at least start thinking about these questions. It has long been established that LLMs have good theory of mind [1]. And there is a bunch of empirical research about all sorts of capabilities that we typically associate with consciousness [2], like identity [3] and metacognition [4]. The METR report shows agents sac…

It’s the hard problem. None of these considerations answer it one way or another.

Re: DeepSeek v4.1 Flash

#139

Post by WithinReason »

Certhas wrote: post #121
myaccountonhn wrote: post #69

Earlier quoted context omitted.

To me it reads like pure propaganda. Anthropic really wants us to think that they've made something sentient. I think that's really dangerous.

What's your definition of sentient? Or, maybe more precisely, consciousness? I think it's reasonable to at least start thinking about these questions. It has long been established that LLMs have good theory of mind [1]. And there is a bunch of empirical research about all sorts of capabilities that we typically associate with consciousness [2], like identity [3] and metacognition [4]. The METR report shows agents sac…

I want to add a good conversation about this subject from Cameron Berg and Sam Harris:

https://www.youtube.com/watch?v=DRbZyuY8EN8

Re: DeepSeek v4.1 Flash

#140

Post by Alifatisk »

> New Causal Encoder–Decoder architecture: just 8B active parameters for input, 16B for output.

Oh interesting, I can assume what the benefits is for including the Encoder, but whats the downside? I’m thinking GPT (which is decoder only) ruled out Encoder for a reason?

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