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Kimi K3: The open-weights escalation

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  • Core argument: Moonshot AI’s Kimi K3 marks a watershed — the open/closed frontier gap narrows from an estimated 6-9 months to roughly 3-5 months, escalating both the upside (diffusion) and downside (risk) of open AI.
  • Technical points: 2.8T-parameter MoE with Kimi Delta Attention and Attention Residuals, ~2.5x scaling-efficiency gain over Kimi K2 via a Stable LatentMoE framework activating 16 of 896 experts; ranks #2 on Vals AI, #3 on Artificial Analysis’s Intelligence Index (behind Claude Fable and GPT-5.6 Sol Max), #1 on Frontend Code Arena.
  • Argues open models are simultaneously “decelerationist” for frontier labs (margin pressure) and “accelerationist” for broader AI diffusion, with Chinese labs showing superior capital efficiency.
  • Practical takeaway: a several-month open/closed buffer is preferable policy ground to heavy-handed bans, which offer false security while merely delaying diffusion — independent evaluation capacity is the more urgent governance gap.