China's K3 Model Reveals the Problem With Open Weights

My benchmarks: https://unlock-ai.natebjones.com/benchmarks/kimi-k3?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true Full post: https://natesnewsletter.substack.com/p/kimi-k3-open-weights-cost?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true Kimi K3 is Moonshot's new open-weight AI model, and it complicates the story that Chinese open models are cheap, efficient, and closing the gap on the frontier. Here's what it actually costs to run, and what it means for OpenAI, Anthropic, and the future of open source. My Links 🔗 👉🏻 Newsletter: https://natesnewsletter.substack.com/ 👉🏻 X: https://x.com/natebjones 👉🏻 TikTok: https://www.tiktok.com/@nate.b.jones 👉🏻 Instagram: https://www.instagram.com/nate.b.jones What's really happening with China's new open-weight AI model? The common story is that Chinese open models are cheap, efficient, and catching the frontier, but the real question is what K3 costs to run and what still needs a closed model. In this video, I share the inside scoop on Kimi K3 and the real economics of open-weight AI: - Why downloadable weights still need 64 accelerator chips to run - How K3's heavy token use erodes its apparent price advantage - What the "efficient Chinese model" narrative gets wrong about serving - Why open weights raise real cyber and governance risks K3 is a genuinely strong open model and a useful pricing check on the closed labs, but treating open weights as cheap, safe, or frontier-equal will cost you. Chapters: 00:00 Kimi K3 is Moonshot's new open-weight model 00:53 Why K3 is a big, heavy model to run 06:20 The cheap-and-easy open source narrative is outdated 14:05 Governments may restrict model distribution 17:04 Why K3 is an inflection point in open source Listen to this video as a podcast. Spotify: https://open.spotify.com/show/0gkFdjd1wptEKJKLu9LbZ4 Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-news-strategy-daily-with-nate-b-jones/id1877109372