Traditional narrative is that you need tons of traces of actual execution to post-train and get models right. Nobody seems to use Kimi API from Moonshot, I bet everybody is using them on neoclouds/inference providers like Together, Nebius, Fireworks etc. where unlikely they will get traces (in fact, thats the whole promise of these inf providers). How are Kimi models improving so quickly? Is this just distillation (though Sol/Fable just came out so I find it hard to believe)
Kimi K3: Open Frontier Intelligence
381–390 of 1001 posts
Re: Kimi K3: Open Frontier Intelligence
#382More details: - https://platform.kimi.ai/docs/guide/kimi-k3-quickstart - https://platform.kimi.ai/docs/pricing/chat-k3 1M context, pricing is $3/$15 for 1M tokens (cache $0.3), which is extremely high for a Chinese open-weight model, but if it's truly competitive with most of the current frontier and is only behind Fable/Sol, the pricing is justified. This is 1:1 pricing of Anthropic's Sonnet series (except Sonnet 5…
also its pretty big model inference costs are high even with margins running a 2.8T model costs a lot. if they release oss may be it goes down to $10-12 per million tokens.
Re: Kimi K3: Open Frontier Intelligence
#383Earlier quoted context omitted.
[flagged]
> I pretty sure OpenAI and Anthropic are doing the same or worse. No they're not. It would end both companies if they were ever found to be doing that. Their terms are clear - if you use the coding plans they can[0] train in return. Enterprise and API, absolutely not. The argument here is that with the Chinese labs you have zero legal recourse. [0] opt-in, thanks
Are we talking about the company sending back private information through its client to « fight » model distillation?
Re: Kimi K3: Open Frontier Intelligence
#384Re: Kimi K3: Open Frontier Intelligence
#385Crap, the first open weight model that really feels out of reach when it comes to running it locally at home. :-(
If DeepSeek v4 flash is run using Q2, then people should run this one using Q½ or maybe Q¼
Re: Kimi K3: Open Frontier Intelligence
#386> Chip Design
> As an early proof of concept, Kimi K3 designed a chip to serve a nano model built on its own architecture. In a single 48-hour autonomous run, K3 built, optimized, and verified the chip using open-source EDA tools on the Nangate 45nm library. Within 4 mm², the chip closes timing at 100 MHz and sustains over 8,700 tokens/s decode throughput in simulation, packing 1.46M standard cells, 0.277 MB of SRAM, and an INT4 MAC array with fused dequantization. A chip built by a model, for a model, reflects K3's long-horizon agentic capabilities.
Absolutely wild.
Re: Kimi K3: Open Frontier Intelligence
#387Earlier quoted context omitted.
I have severe complaints about Anthropic's product managers on this front. Their preference for hiding, obscuring, and trying to wrest control from the user are a bit harrowing. It would be wonderful to go back to Claude Code from before March. It seems like every release destroys value for me!
It's a defensive tactic to reduce the effectiveness of distillation. Say of that what you will, but it's not because they want to wrest control from users. It's because they don't want Chinese companies to do exactly what Moonshot (Kimi creators) and others have done.
Anthropic’s position being that it is entitled to train models on the creative works of anyone at any time, but its own slop generators’ outputs are sacred jewels that must be protected from being learned from.
Re: Kimi K3: Open Frontier Intelligence
#388I mean, it's hard not to be impressed by the Moonshot team. Absolutely great work.
Re: Kimi K3: Open Frontier Intelligence
#389Some official benchmark numbers posted in Chinese social media (I am sure they will publish an English blogpost later too): https://mp.weixin.qq.com/s/V4xhEIy8xDXSMDPrPkmUAQ Generally looks like a Sol/Fable tier model, better across the board than Opus 4.8. (Edit) English blogpost is up now: https://www.kimi.com/blog/kimi-k3
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
> If the numbers hold up scrutiny, this is scary good.
After using it for a few hours, I believe these benchmarks.
Re: Kimi K3: Open Frontier Intelligence
#390Is there a way to try it without using your Google account or giving them your phone number?