Rob Shocks 拆解 Vercel 换用 Jev 后快 6 倍
发布周实测：Jev 每十亿 token 约 42 美元、单次回答约 100ms，智能家居 demo 里 185ms 直接输出可执行选择。
Rob Shocks says Vercel pulled a cheap classifier, dropped in Jev, and got 6x faster on the same job - the reason it's cheaper than anything he's used shows up halfway through. this is his launch-week breakdown, and most of it happens live in the playground, not on slides. $42 per billion tokens → about 100ms per answer → 6x faster at Vercel → "it basically saturated the eval" "If you want chat, this is not the model for you." - Rob, in the first two minutes the part that got me is the smart home demo. "turn off all of the lights", and the mock house goes dark in 185 milliseconds. no text comes back, just a choice the code can run. Jev is TypeSafe's System One model, led by GPT-4 co-author Diogo Almeida. he also shows it playing Doom for an hour for around $7. bookmark & watch today ↓
这条是引用着另一条写的：「长文：如何搭好 Jev 驱动的 agent 技术栈」