Kimi K3: Open Frontier Intelligence

Post by rsanek » Fri, Jul 17, 2026, 1:42 AM UTC

adverbly wrote: post #218

ekojs wrote: post #37

> In our evaluations, Kimi K3 delivers frontier-level performance. Among the models tested, its overall intelligence ranks second only to Claude Fable 5 and GPT-5.6 Sol. For the complete benchmark results, see our tech blog. The full model weights of Kimi K3 will be released in the coming days. More details on the architecture, training, and evaluation will be published together with the Kimi K3 technical report. > K…

> 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.

Post by rsanek » Fri, Jul 17, 2026, 1:43 AM UTC

efficax wrote: post #341

adverbly wrote: post #218

Earlier quoted context omitted.

> 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.

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

Post by hkalbasi » Fri, Jul 17, 2026, 1:46 AM UTC

Post by ethbr1 » Fri, Jul 17, 2026, 1:51 AM UTC

Analemma_ wrote: post #626

x313 wrote: post #518

Earlier quoted context omitted.

If there was some grand strategy for all Chinese labs, surely it'd have leaked by now. I think its more likely that: - Companies can still make money from commodities - Chinese labs only have 5-10% the valuation of OpenAI/Anthropic, so massive monopoly profits aren't necessary. Profit expectations for tech companies in China are really low in general, complete opposite of the US. - Open weighting is a great way to ge…

- AI investment is basically the only thing keeping the American economy treading water at the moment, and kicking the chair out from under that industry benefits China tremendously. I'm definitely not saying that's the only factor, but I think it's naive to assume it isn't at all a factor.

Post by dominotw » Fri, Jul 17, 2026, 1:55 AM UTC

echelon wrote: post #301

GodelNumbering wrote: post #259

Earlier quoted context omitted.

The link has 6 well-known benchmarks where this beats Fable (out of 14 I counted). If the numbers hold up scrutiny, this is scary good. Forget about their pricing but the companies that do have means to host such models fully on-prem are also the same companies that are paying tens of millions of $ in inference cost every month, and are by extension the biggest customers of OAI and Anthropic

Open Source >>> Closed Source [1] I don't want to cheer against my country, but we've given up on open source. The way Anthropic and OpenAI treat their customers as adversaries is embarrassing. I will cheer for China, for Kimi, and for z.ai until we have something in the same category. [1] I'd even be fine with open weights, fair source, or anything that let us have direct access to the weights. Even if that came wit…