Kimi, every mention
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every year anyone Philip Kiely 10Mark Bissell 7Doug O'Laughlin 7Kyle Kranen 6Shawn Wang 4Elie Bakouch 4Alessio Fanelli 3Dylan Patel 2Ari Morcos 2Ahmad Awais 2
Verbatim, from the transcripts: the passages where Kimi comes up
The Inference Frontier: from 100 to 10,000 tokens per second — Sean Lie, Cerebras CTO
Next 100x in AI: Inference, Networking, & Self-Optimizing Models — Philip Kiely & Ali Taha, Baseten
- ▶ 13:09 Alessio Fanelli Like, I think it was with, uh, Kimmy K-II .5 or GLM five two, the latest, there was sort of an inference war, right?
- ▶ 14:38 Philip Kiely K, uh, two five to two six was, like, pretty, pretty similar.
- ▶ 14:38 Philip Kiely K, uh, two five to two six was, like, pretty, pretty similar.
- ▶ 16:14 Philip Kiely I mean, Kimmy K two had, oh, sorry, uh, GLM five two had.
- ▶ 16:40 Philip Kiely So something that, uh, Haley, a guy on our team, if, if we could take a look at this, um, he, like, kind of grafted the Kimi, um, vision encoder onto GLM 5.2.
- ▶ 29:02 Philip Kiely I think Kimi in particular does a good job of vendor benchmarking here. 4 times in the scene
- ▶ 41:34 Philip Kiely Um, like Kimmy, uh, uh, GLM five, two has its own MTP, right?
- ▶ 1:08:32 Alessio Fanelli I think on your guys' end, you see a lot of, okay, one day it's GLM, Kimmy, DeepSeq, uh, Minimax, throw in the others.
- ▶ 1:11:30 Alessio Fanelli One, the latest Kimi, which is really big, uh, three trillion.
- ▶ 1:14:45 Ali Taha And it's one of those spaces where the, the open source models are, like with LLMs, we see Kimi K-III is almost comparable to, you know, Mythos or like GPT-Five.
- ▶ 1:34:48 Philip Kiely Just coding model that we had access to, and it would do an equally good job of optimizing, uh, DeepSeq or Kimi or something.
The AI Frontier: from open weights to open research — Eiso Kant, Poolside AI
- ▶ 24:42 unnamed speaker We're very much like, ah, okay, look, it's like, you know, on par with Kimmy, DeepSeek, whatnot, the small ones, Gemma level.
⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai
- ▶ 14:46 Ronak Malde 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.
⚡️Making DeepSeek v4 outperform Opus 4.7 with Taste — @AhmadAwais , CommandCode.ai
- ▶ 13:50 Ahmad Awais Then I looked at our, you know, logs for last 30 days and Kimi is doing exactly the same thing. 2 times in the scene
AI-Native Engineering: 100% adoption, 5x search throughput, unlimited tokens — Mikhail Parakhin
- ▶ 1:04:25 Mikhail Parakhin And then we run it at a very large scale, like in bad jobs, because just running and it beats in that situation, but very often beats, uh, Quinn or yeah, Kim is more on the reasoning side.
Marc Andreessen introspects on Death of the Browser, Pi + OpenClaw, and Why "This Time Is Different"
- ▶ 31:06 Shawn Wang Kimi, Deep Seek, uh, uh, ZAI, um, Quen, O-One is in there.
Agent Inference at the "Speed of Light" — How NVIDIA moves like a $4.3 Trillion Startup
- ▶ 45:20 Kyle Kranen We see models like Kimi or GPT-OSS. 4 times in the scene
- ▶ 45:25 Kyle Kranen So Kimi II comes out, right? 2 times in the scene
Dylan Patel Explains the AI War While Cooking | In-Context Cooking
- ▶ 13:31 Dylan Patel Kimi K K two five, uh, agent swarms.
- ▶ 23:30 Dylan Patel Uh, now we have, uh, you know, we had Kimi K. 2.5 swarms.
Claude Code for Finance + The Global Memory Shortage: Doug O'Laughlin, SemiAnalysis
- ▶ 34:11 Doug O'Laughlin You know, speaking of that though, you say that, but Kimmy, Kimmy to one agent swarm is actually good. 7 times in the scene
- ▶ 41:11 Shawn Wang And probably that's the only time we'll talk, we'll talk about Kimmy.
⚡️ Reverse Engineering OpenAI's Training Data — Pratyush Maini, Datology
- ▶ 25:01 Pratyush Maini Like even the Kimi K two model has like a long section of like how they do rephrasing of internet content.
Goodfire AI’s Bet: Interpretability as the Next Frontier of Model Design — Myra Deng & Mark Bissell
- ▶ 22:36 Mark Bissell This is Kimi K two. 7 times in the scene
Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith
- ▶ 23:04 Shawn Wang Uh, and Kimmy K two thinking, wow, still hanging in there.
- ▶ 1:04:50 Micah Hill-Smith Kimi K too, is it like three percent active?
[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute
- ▶ 19:21 Andy Konwinski Moonshot, Kimmy, Deep Seek.
⚡ Open Model Pretraining Masterclass — Elie Bakouch, HuggingFace SmolLM 3, FineWeb, FinePDF
- ▶ 8:09 Elie Bakouch The rest of it, I think the model architecture, we, with, like, the Quen, Deepsea, Kimi architecture, we're already at a point where this is already not optimal, but this is, like, pretty, pretty advanced. 2 times in the scene
- ▶ 10:53 Elie Bakouch Uh, we know, for example, that like, uh, Google is using, uh, I mean, we don't know, but like on like old paper, uh, Google are using like other factor, but recently before this, uh, King K-II, everyone was using, uh, Adam. 2 times in the scene
Amp: The Emperor Has No Clothes
- ▶ 28:11 Quinn Slack You have the open source models like Quinn three coder and Kimmy K two, and they're moving so fast.
Better Data is All You Need — Ari Morcos, Datology
- ▶ 37:46 Ari Morcos Um, the Apple paper, the Kimi paper has mentioned this, a bunch of others. 2 times in the scene
The AI Agenda: GPT5 leaks and the business of AI News — Steph Palazzolo, The Information
- ▶ 14:53 Shawn Wang There's a lot of these like Kimi, K two, and what's the other one?