[adverbly]

> 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.

[avianlyric]

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.

[verdverm]

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]

Moonshot announced they will be making weights available by July 27

https://twitter.com/Kimi_Moonshot/status/2077830229968683203

[efficax]

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]

> cost has nothing to do with it

> customers will flock to the cheapest inference

[efficax]

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

[rsanek]

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

[hedora]

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]

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]

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]

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]

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]

Oh really? That's great to know, thanks! I didn't realise Luna was that good.

[bogdan]

To be fair the stock market is a big one