Open models recap: more on Kimi K3, Qwen 3.8, Xi's WAIC speech, distillation, the open-closed gap, and what's next

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• Core argument (co-written with Florian Brand): Chinese open-weight models (Kimi K3, GLM-5.2, Qwen) are closing the gap with Western frontier labs mainly through capital efficiency, focused teams, and better data practices — not primarily distillation of proprietary models.
• Directly rebuts Ben Thompson’s claim that distillation becomes more impactful at the RL stage: grading millions of RL rollouts with an expensive API model “would be insanely expensive,” and literature doesn’t support “the strongest model” as automatically the best teacher — SFT distillation gives incremental, not transformative, gains.
• Chinese-lab advantages cited: mid-20s researchers with singular focus, access to smuggled Nvidia chips plus domestic alternatives (Huawei Ascend), lower labor/compute costs enabling 1-2 month release cadences.
• Practical takeaways: expect rapid third-party fine-tunes of Kimi K3’s “rough-edged” post-training; restricting Chinese open models domestically flips the cybersecurity asymmetry (defenders stop improving, attackers don’t); by year-end expect a US entrant into the “close competitor” tier, a possible Tencent surprise, and model-size scaling plateauing around ~3T parameters.
• Flags a cybersecurity risk baked into the “6 months to live” thesis: banning open Chinese models domestically doesn’t stop attackers from using them, only stops defenders from improving with them.