"Kimi K3 owned the internet today. Read tons of content & observed 10 key patterns: 1) The open source-to-frontier gap went from a year+ behind to 6 months to 6 days, all within the last 12 months. 2) An open model debuted ahead of a flagship US model for the first time ever. Artificial..."
...Analysis scored K3 at 57. Opus 4.8 sits at ~56, GPT-5.6 Terra at 55. It's still behind Fable 5 and GPT 5.6 Sol. 3) K3 helped build itself. An early version of K3 did the majority of Moonshot's own kernel optimization work during development. One 15-hour unattended run made a core operation 2.5x faster. 4) It's cheap per token, not cheap per answer. Sticker price is 1/3 of Fable. But it only runs at max thinking effort and burns ~2x the tokens per response. @simonw measured 13,241 reasoning tokens to write a 3,417 token answer. 5) The era of dirt-cheap Chinese AI is ending. $3/$15 per million tokens. Hacker News called it "extremely high for a Chinese open-weight model." 6) Weights don't drop until July 27. Mentions of "open" quietly disappeared from the docs an hour after launch. 7) Even when the weights drop, you can't run them. 2.8 trillion parameters. Top Reddit joke: "2TB VRAM Is All You Need." Open weights increasingly means auditable by companies with GPU clusters, not runnable by you. 8) The "they just distill/copy" argument is dying in public. One of the most upvoted comments: you'd have to be "a complete ignorant or a complete bigot" to believe Chinese labs aren't legit at this point. 9) Day one user verdict: fast, but less accurate. "Faster than Claude, but less accurate. On par with GPT 5.5 perhaps, but not 5.6 or Fable." 10) The one thing everyone agrees on: competition is wonderful. Even the skeptics: "Say what you want about these Chinese models but they sure create competition and urgency in the space." — Alex Lieberman
Source: https://x.com/businessbarista/status/2077933640428707860
Introducing Kimi K3: Open Frontier Intelligence
2.8 Trillion Parameters, 1 Million Context, Native Multimodal Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts Attention Residuals deliver ~25% higher training efficiency at <2% additional — Kimi.ai
Source: https://x.com/Kimi_Moonshot/status/2077830229968683203