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> Maybe another DeepSeek moment right here. Surely not... What made DeepSeek disruptive was that the cost was 10X lower. In this case, the cost is about 2X lo

> Maybe another DeepSeek moment right here. Surely not... What made DeepSeek disruptive was that the cost was 10X lower. In this case, the cost is about 2X lower the Sol I think? At 2X, you're pretty close to the error margins due to token efficiency etc... I'd say this is "on trend" for open models catching up to frontier labs, but its not a "change in the trend" like DeepSeek was IMO.

hedora 3mo ago
DeepSeek didn’t really change any trends though, unless you count the stock market. It was impressive work, but models were commoditizing and inference costs were dropping rapidly already. They were neither the first nor the last 10x optimization, from what I’ve seen.
- stavros 3mo ago
  If you know of any other 10x optimisations currently, please let me know! I'm in the market for a model that's a tenth the price of a frontier model at the same level of quality.
  - ac29 3mo ago
    You do understand that the "frontier" people are usually talking about is the cost-intelligence frontier right? By definition there is no model that is both cheaper and as intelligent or better than another on the frontier.
    - stavros 3mo ago
      OK, let me be more precise: If you know of a frontier model that's ten times cheaper than the previous frontier model at that level of intelligence, please let me know, I'm in the market for one. Is that better?
      - ac29 3mo ago
        Its just a single benchmark, but Luna 5.6 xhigh scores within the margin of error the same as Opus 4.8 max on DeepSWE for 8x cheaper. Luna max is quite a bit higher than Opus and still 4x cheaper
        stavros 3mo ago
        Oh really? That's great to know, thanks! I didn't realise Luna was that good.
- bogdan 3mo ago
  To be fair the stock market is a big one
avianlyric 3mo ago
It was also disruptive because it was open weight, meaning anyone and their dog could theoretically compete with the frontier labs for their inference revenue. The frontier labs need to recoup a huge amount of cash to cover their model development costs, and justify their valuations. That’s plausible when they’re only ones capable of selling inference on these models, it a lot less plausible when models themselves become cheap commodities, and you’re just competing on your ability to provide compute. Anthropic and OpenAI can’t compete with people like AWS on that front.
efficax 3mo ago
cost has nothing to do with why deepseek was disruptive, the fact that it means there is zero moat around anthropic or openai is what's disruptive about it. it means in the mid-term LLMs will be commoditized and customers will flock to the cheapest inference wherever they can find it. there's no reason to stick to the "frontier" labs
- rsanek 3mo ago
  > cost has nothing to do with it > customers will flock to the cheapest inference
  - efficax 3mo ago
    if deepseek cost twice as much to train it would prove the same thing: the american companies have no monopoly on state of the art llms, and commoditization is happening
verdverm 3mo ago
It's different, but similar. If they release the weights, then we have a Fable / frontier model people can tinker with. Either way, it's still quite impressive and knocked a US company out of the top three (google). How long before China dominates the top-10 (if they don't already) or the #1 model?
- verdverm 3mo ago
  Moonshot announced they will be making weights available by July 27 https://twitter.com/Kimi_Moonshot/status/2077830229968683203 https://twitter.com/Kimi_Moonshot/status/2077830229968683203
ds2 3mo ago
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rsanek 3mo ago
If AA is to be believed then per-task it is about the same cost as Sol. Agree that it's very different from DeepSeek v4 Pro, which is ~15x cheaper than K3. https://artificialanalysis.ai/models/kimi-k3#price-cost https://artificialanalysis.ai/models/kimi-k3#price-cost

hedora 3mo ago

DeepSeek didn’t really change any trends though, unless you count the stock market. It was impressive work, but models were commoditizing and inference costs were dropping rapidly already. They were neither the first nor the last 10x optimization, from what I’ve seen.

stavros 3mo ago
If you know of any other 10x optimisations currently, please let me know! I'm in the market for a model that's a tenth the price of a frontier model at the same level of quality.
- ac29 3mo ago
  You do understand that the "frontier" people are usually talking about is the cost-intelligence frontier right? By definition there is no model that is both cheaper and as intelligent or better than another on the frontier.
  - stavros 3mo ago
    OK, let me be more precise: If you know of a frontier model that's ten times cheaper than the previous frontier model at that level of intelligence, please let me know, I'm in the market for one. Is that better?
    - ac29 3mo ago
      Its just a single benchmark, but Luna 5.6 xhigh scores within the margin of error the same as Opus 4.8 max on DeepSWE for 8x cheaper. Luna max is quite a bit higher than Opus and still 4x cheaper
      - stavros 3mo ago
        Oh really? That's great to know, thanks! I didn't realise Luna was that good.
bogdan 3mo ago
To be fair the stock market is a big one

avianlyric 3mo ago

It was also disruptive because it was open weight, meaning anyone and their dog could theoretically compete with the frontier labs for their inference revenue. The frontier labs need to recoup a huge amount of cash to cover their model development costs, and justify their valuations. That’s plausible when they’re only ones capable of selling inference on these models, it a lot less plausible when models themselves become cheap commodities, and you’re just competing on your ability to provide compute. Anthropic and OpenAI can’t compete with people like AWS on that front.

efficax 3mo ago

cost has nothing to do with why deepseek was disruptive, the fact that it means there is zero moat around anthropic or openai is what's disruptive about it. it means in the mid-term LLMs will be commoditized and customers will flock to the cheapest inference wherever they can find it. there's no reason to stick to the "frontier" labs

rsanek 3mo ago
> cost has nothing to do with it > customers will flock to the cheapest inference
- efficax 3mo ago
  if deepseek cost twice as much to train it would prove the same thing: the american companies have no monopoly on state of the art llms, and commoditization is happening

verdverm 3mo ago

It's different, but similar. If they release the weights, then we have a Fable / frontier model people can tinker with. Either way, it's still quite impressive and knocked a US company out of the top three (google). How long before China dominates the top-10 (if they don't already) or the #1 model?

verdverm 3mo ago
Moonshot announced they will be making weights available by July 27 https://twitter.com/Kimi_Moonshot/status/2077830229968683203 https://twitter.com/Kimi_Moonshot/status/2077830229968683203

ds2 3mo ago

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rsanek 3mo ago

If AA is to be believed then per-task it is about the same cost as Sol. Agree that it's very different from DeepSeek v4 Pro, which is ~15x cheaper than K3. https://artificialanalysis.ai/models/kimi-k3#price-cost https://artificialanalysis.ai/models/kimi-k3#price-cost