Kimi

“The one thing we all knew in startup world is that if I have a two-year lead on you, and you try and cast me by hiring a thousand engineers, you're gonna wreck your company. Like, that never works. It's a mythical man month. Nine women can't have a baby in a m…”

“You still have to run inference like GLM or Kimi. Kimi is very expensive to serve. The cost per answer is significantly higher.”

“It's not cyber capable in the way, the same way the frontier models are and long range, long horizon tasks. I think it's still a bit behind the frontier models, but.”

“GLM 5.2 was a really big, big step for open weight models. Kimmy was kind of like moonshot getting up to that step. That's a little bit how I see it.”

“It's not, you know, it got to a 56% on MMLU Pro, I think, so not, not quite Frontier, but if you're running this model, you haven't suffered any loss on your GLM-Five-II quality.”

“You need GB 300 to fit it on a single node. It's simple math. NVFP four, 2.8 trillion parameters 1.4 terabytes. The GB 300 have 288 gigabytes each. So across eight of those you have enough room For the model”

“And I'll make this prediction here, that you're going to see some of the major customers Of Anthropic and major customers of OpenAI. I'm talking about the eight and nine figure customers, people spending fifty million, a hundred million a year. They're leaving…”

“What I think is kind of happening right now, but like clawed kind of mother birds into, Kimmy too, and then now Kimmy too is post-training thinking machines, and so it just keeps going and going.”

“The Chinese open source, open rate models were available, and I think they use Kimi or Kuan or one of the newest models to help them figure out what happened, right? So they were able to defend themselves using an open source model, and then they do this blog …”

“This is not a tiny efficient model. This is 2.8 trillion parameters. It's going to require a ton of compute to serve.”

“What you've seen is a lot of these tiny labs faced with compute constraint and in some ways capital constraint, they're forcing them to specialize rather than compete across every dimension. So, you know, for the sake of, you know, deep seek, it's really, real…”

“I think both, you know, DeepSeek and Kimi, if not seen as kind of the top two labs right now coming out of China, both founders have openly talked a lot about management of people you know, removing distractions, really focused on the pursuit of AGI, not kind …”

“I was offered Kimmy today, by the way, Rory at 20 Berlin. This was the, it fell into my inbox. I have an SPV for you. Do Kimmy at 20 Berlin. We're oversubscribed, but we'll make room for five million for Harry.”

“You can just ask GPT-V to go find these bugs and it will go do it for you. You can just ask Kimi, which is an open source Chinese model. It will go write you these exploits.”

“I think America or the Western world has some work to do still. Like obviously having one trillion parameter models like Kimi or like an amazing models like GLM and DeepSeq, I don't think we're quite there yet for that size of model.”

“Now when you look at reinforcement learning from models like Kimi or from DeepSeq models, it seems that they are closer to one million data points.”

“To just run the swarm, I think it's like a 16 node of H-one hundreds.”

“I can run Minimax two one, which is I would say is, is the best open source model right now, although Kimi just came out and I haven't had a chance to try it yet, so, so we'll see how that goes.”

“Quark, which is Alibaba's AI assistant on both web and mobile. Daobao, which is ByteDance's AI assistant on also on both web and mobile. And then Kimi, which is another general AI assistant from Moonshot AI. Each of those ranks, actually all of them in the top…”