Snapshot · This Week in Tech (Audio)
DeepSeek V4 costs ~$0.12 per million tokens, vs $10+ for Claude Fable, illustrating the dramatic price gap between Chinese open-weight and American closed frontier models.
Where this was said
At 50:06 · chapter starts 47:50
Leo Laporte walks through Dean Ball's influential tweet thread, now that Ball has become OpenAI's head of Strategic Futures. Ball's argument has four points: Kimi K3 is genuinely impressive and cannot be explained away by distillation; China allowing its release is strategically surprising; open-weight models deter AI capex by making private investment in frontier models irrational; and an open-weight dominant world is essentially AI communism — state-provided digital infrastructure rather than a market product. Harper Reed takes sharp issue with Ball's framing, calling the 'China is just too stupid to know what it's doing' angle a 'fatal flaw' in most US analyses of China. Leo reads Ball's final warning: at some point these models will be capable enough that a non-living, self-replicating agent escaping from a Chinese lab will be a real concern. Harper responds that US labs haven't been blameless about training data copyright either, and that the real question is how America competes in a game it's not currently playing.
Harper Reed used Claude Code back in early 2025 when it was still rough. Today's GLM is at least as good as that version of Claude — and it's effectively free. The only question is how much time separates frontier from open-weight models. If the gap is 6 months and the open-weight version is free, why pay?
Anthropic's revenue run rate grew from ~$60B to $67B even after DeepSeek's shock debut, showing cheap Chinese models have not yet collapsed American lab economics.
For everything except hard-core coding, open-weight models are already good enough. Harper Reed's Toyota Corolla analogy nails it: a Corolla is a completely rational car. It does the thing. You might prefer something else, but 'better' doesn't mean 'worth paying 50x more for.'
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