FrontierCS 2 - Closed-loop action sampling: leaderboard

FrontierCS 2 selected formal runs on 48 research engineering tasks, with each source-native coding harness. Paper v1 Table 3 fixes the effort settings; the subsequently added DeepSeek 1017 row leaves effort unspecified. Superseded attempts are not selected by score. Native bounded task scores are distinct from human-reference margins and from pass/fail verdicts. Explicit failed-run zeroes remain zero; unreported scores remain missing. Metric: Task score (0–100).

Metric: Task score (0–100). Source: frontier-cs.org. Saturation forecast: Around 2029. 14 models tracked.

Top models

#ModelScoreOverall rank
1GLM-5.3 (Max)59.81#39 (GLM-5.3)
2Claude Opus 5.5 (Max)57.12#5 (Claude Opus 5.5)
3Muse Wonder (Max)55.44#15 (Muse Wonder)
4DeepSeek V4.1 Flash (Max)53.33#35 (DeepSeek V4.1 Flash)
5Gemini 4 Argon (High)52.77#8 (Gemini 4 Argon)
6GPT-6.1 Sol (xHigh)52.55#7 (GPT-6.1 Sol)
7GPT-6 Astra (xHigh)51.95#6 (GPT-6 Astra)
8DeepSeek V4.1 Flash (1017)51.49#27
9Kimi K3 (High)50.88#33 (Kimi K3)
10Muse Spark 1.3 (High)44.47#29 (Muse Spark 1.3)
11GLM-5.3 Flash (Max)15.88#72 (GLM-5.3 Flash)

No result here: #9 Claude Fable 5.1, #10 Muse Wonder Full.

Interactive version: theaggregate.ai/benchmark?slug=frontiercs-2-closed-loop-action-sampling · How It Works · Data refreshed daily, snapshot 2026-10-26.