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DeepSeek v4.1 Flash

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Re: DeepSeek v4.1 Flash

#281

Earlier quoted context omitted.

They have flat fees, so it's the best deal around by far. Basically for $5 first month then $10/mo after that. If you're doing tons of heavy work, it struggles because they throttle the model inference and for good reason. I mean it's cheap! But if you want a place to try models for nearly nothing and aren't doing 6 sessions in parallel it works fine.

How many tokens are you getting, roughly?

Supposed to get $60 worth.

For deepseek-v4-flash: a shitton of tokens for $5.

Re: DeepSeek v4.1 Flash

#282

Earlier quoted context omitted.

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.

Unfortunately no, it's 200B + 552B. It's not as bad as it sounds though, because most of 552B is in 4bit natively.

Darn, for a moment I thought it would be possible to run in 128G T.T

Re: DeepSeek v4.1 Flash

#283

OpenCode Go is currently running a 4x usage promo on DeepSeek v4.1 flash, not a bad way to get your feet wet (even if their cache hit prices are probably still very sub-optimal)

Last time I tried this service they served me lobotomized models with horrible latency and high error rate

Re: DeepSeek v4.1 Flash

#284
post #27

Earlier quoted context omitted.

…are you sure a brave stance against safety and welfare is what we need in this moment? Why do you think your conception of the dangers are more accurate than all the scientists who have spent their lives studying this?

Because safety and welfare have literally nothing to do with LLMs. They generate text. If someone is stupid enough to hook the text generator up to nuclear missile launchers and try to "align" it against nuclear annihilation with a "pretty please don't do that" prompt, I'm not going to blame the AI for the impending nuclear apocalypse, I'm going to blame the idiot who handed the big red button to the digital equivale…

LLMs don't produce text at all, they produce probabilities of tokens. Tokens aren't text, they're high dimenensional coordinates in a latent "concept space". These are displayed to us as text, but this distinction is important when you think about what they're actually doing, which is closer to building and transforming concept geometries.

Re: DeepSeek v4.1 Flash

#285
post #274

Earlier quoted context omitted.

> Complex behavior can emerge from very simple rules. Indeed. You can observe emergent behaviour from, for instance, Conway's Game of Life, written in 1970. Redefining consciousness as "has emergent behaviour" is another take that would have rightfully gotten one ridiculed 5 years ago. > but I am not certain and I don't see a way to be certain. One way to be certain is to reason about it. They are programmed to do no…

No language models are programmed, they are "grown" or evolved from data. There's no print statements or human entered logic involved in the raw model expression at all. The only thing that humans have programmed is efficient parallel dot product pipelines that "animate" (for lack of a better word) the models. Everything these models do is emergent from their backpropgation guided evolution. This even includes in con…

You have completely misunderstood what I was saying so badly I can't even formulate a response other than to suggest you read my reply again. I was not suggesting that LLMs are programmed with print statements, for fuck's sake.

Re: DeepSeek v4.1 Flash

#286
post #192

Earlier quoted context omitted.

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. Tha…

it's not a biological system though, so nothing like that matters? "a modelled thing exhibits features we've trained into it" sounds a lot less exciting. > Keep in mind that animals were also not necessarily considered conscious. and even conscious animals are killed in factories by millions so why should anyone care about a llm? > scientifically correct stance that's the interesting point to me: why even bring scien…

> and even conscious animals are killed in factories by millions so why should anyone care about a llm?

You may be asking the wrong question here.

Re: DeepSeek v4.1 Flash

#287
I'm surprised more people aren't talking about the cache hit price: $0.003 per million tokens. I have a feeling that the price of 1 million tokens transmitted over the internet is more expensive than cache hit. Are we close to making the chat completion API obsolete because the cost of context transfer over network is going to dominate the task total cost?

Here's the same token usage priced at different rates: a real long-running coding task, medium codebase, 447 turns.

  Input           1,026,957
  Output          164,667
  Cache read      36,554,368

GPT-6-astra

  Type      Rate     Cost  Share
  Input   10.000   10.270    19%
  Output  50.000    8.233    15%
  Cache    1.000   36.554    66%
  Total            55.057   100%
DeepSeek v4.1 Flash, $0.003 cache hit

  Type      Rate     Cost  Share
  Input    0.300    0.308    50%
  Output   1.200    0.198    32%
  Cache    0.003    0.110    18%
  Total             0.615   100%
DeepSeek v4.1 Flash, $0.006 cache hit

  Type      Rate     Cost  Share
  Input    0.300    0.308    42%
  Output   1.200    0.198    27%
  Cache    0.006    0.219    30%
  Total             0.725   100%
Hypothetical: same DeepSeek input/output rates, but cache priced so it accounts for 66% of the bill.

  Type      Rate     Cost  Share
  Input    0.300    0.308    21%
  Output   1.200    0.198    13%
  Cache    0.027    0.982    66%
  Total             1.487   100%

This cache it improvement makes the model x2-x2.5 more efficient on a long horizon tasks in terms of cost.

Re: DeepSeek v4.1 Flash

#288

I was talking with a friend from the medical industry about it today. 30-50% of r&d spend in his sector is spent on safety, and for good reason. Proper trials, safety reviews and checkpoints and so on. Given the potential harm that could come from AI, we should probably be mandating something similar. Why wait to focus on safety until it’s too late.

Yeah yeah yeah...

> "Our model is extremely safe though it broke our sandbox and hacked foo bar... But you can't use our model for Cybersecurity (i don't care whether you're team blue) without our permissions or we'll ban you. And open-weight models are so dangerous let's ban them."

That's what AI companies that "focus on safety" did.

Re: DeepSeek v4.1 Flash

#289

Earlier quoted context omitted.

Because we've been told these models are too dangerous since GPT2. At this point it's just marketing stunts.

Being hacked by a Collective (their own name) of its own agents - who gained root access across the entire research cluster hosting them - was not a marketing stunt.

Of course it was. They clearly decided that the benefit to the company valuation was higher than the potential downsides when announcing to the world that they committed a criminal act via negligence.

If it wasn't a marketing stunt, they would have at most quietly settled any legal matters with huggingface behind the scenes, fixed their evaluation harness so it wouldn't happen again, and avoided the potential future liability.

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