Rohan Paul· @rohanpaul_ai · X·· 2026-07-24AI 评分42
AI 导读
Offloop 的 4 人团队用多智能体系统在 GDPval 基准上以每任务 $1.65 的成本取得 84.9 分，超越 Claude Code（82.4 分，$14.38/任务）和 Codex（83.3 分，$5.20/任务）。该系统还在 GDP.pdf 和 JobBench 上达到 SOTA，成本仅为竞品的 1/3 到 1/10。
正文 · 原文
So much recent work and research papers points to the same thing: the "harness" is becoming the real capability layer.
@Offloop 's 4-person team demonstrated a multi-agent harness outperforming Claude Code and Codex on GDPval benchmarks, targeting $2.4T in US knowledge work.
- The team scored 84.9 at $1.65 per task.
- Opus 4.8 inside Claude Code scored 82.4, and GPT 5.6 Sol inside Codex scored 83.3, costing far more per task, $14.38 and $5.20
GDPval measures how well AI handles real work across 44 occupations and 9 major industries. Models get shell access and web browsing, then face blind pairwise comparisons against human experts.
And those tasks map onto US jobs paying roughly $2.4T a year.
In our internal evaluations, Offloop achieved new state of the art results on three benchmarks evaluating professional knowledge work: 84.9 on GDPval, 44 on GDP.pdf, 67.2 on JobBench - each ahead of Codex and Claude Code, at 1/3 to 1/10 of their cost per task. Lower cost per completed task means agents you can leave running, more tasks per dollar, and margins that survive scale.在 X 查看被引用的帖子
来源：Rohan Paul · x.com