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受 Jev 启发做高速浏览器 agent

作者让 Codex 接管 2×B300 上的 vLLM,从 harness 到推理全面改造,在 12 个本地表单任务上追求「分数不低于基线的前提下端到端最快」。

Gregor Zunic
@gregpr072026.09.22收录原推发布于 2026.09.21
受 Jev 启发做高速浏览器 agent
Gregor Zunic @gregpr07原推发布于 2026.09.21
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Jev really inspired me to build SUPER fast browser agents without sacrificing accuracy. I gave Codex access to vLLM on 2×B300 and let it change everything from the harness to inference. The constrained optimization: > min end-to-end task time > s.t. score ≥ baseline Caching, thinking, action batching, inference. Any part of the pipeline is fair game. First results below on 12 local form tasks. The goal: 10× faster on long tasks.

x.com/gregpr07/status/2101875560515518732采集于 2026.09.22 10:20