Tencent WorkBuddy Bench – Agentic Coding Leaderboard
GLM-5.2’s two Security leads are paid for in tokens (30–31k per run on both harnesses), and its 77.06 on Code under Claude Code costs 22.0k against GPT-5.5’s 8.7k; the smallest Claude Code point on the Code chart — Claude Opus 4.8 at 4.7k — comes from its modified-instruction run (see the leaderboard notes). Turns count unique assistant messages including subagent activity; output tokens come from each run’s final usage.
- ▪GLM-5.2’s two Security leads are paid for in tokens (30–31k per run on both harnesses), and its 77.06 on Code under Claude Code costs 22.0k against GPT-5.5’s 8.7k; the smallest Claude Code point on the Code chart — Claude Opus 4.8 at 4.7k —
- ▪Turns count unique assistant messages including subagent activity; output tokens come from each run’s final usage.
Opening excerpt (first ~120 words) tap to expand
01 Key Takeaways核心结论 No single model dominates — column leadership splits across subsets and harnesses: Claude Opus 4.8 leads five of the eight scored columns (Code on both harnesses 74.43 / 77.90, Web on both harnesses 68.14 / 69.86, Office on CodeBuddy Code 82.37), GLM-5.2 two (Security 76.32 / 80.86 on both), GPT-5.5 one (Office 86.05 on Claude Code).没有一家通吃：各列榜首分散在不同子集与 harness 之间:Claude Opus 4.8 拿下八个计分列中的五个(Code 双 harness 74.43 / 77.90、Web 双 harness 68.14 / 69.86、CodeBuddy Code 下 Office 82.37),GLM-5.2 两个(Security 双 harness 76.32 / 80.86),GPT-5.5 一个(Claude Code 下 Office 86.05)。 An open-weight model holds its own: GLM-5.2 tops Security under both harnesses — two of the eight columns — and stays within a point of the Code lead under Claude Code; open-weight competitiveness here is…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Workbuddybench.
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