FrontierCS 2 - Private Set List Decoding: 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 Superseded attempts are not selected by score.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 2030. 14 models tracked.

Top models

#ModelScoreOverall rank
1GPT-6.1 Sol (xHigh)58.19#7 (GPT-6.1 Sol)
2Muse Wonder (Max)58.06#15 (Muse Wonder)
3GPT-6 Astra (xHigh)56.32#6 (GPT-6 Astra)
4Gemini 4 Argon (High)56.12#8 (Gemini 4 Argon)
5DeepSeek V4.1 Flash (1017)55.33#27
6Claude Opus 5.5 (Max)55.26#5 (Claude Opus 5.5)
7Kimi K3 (High)54.7#33 (Kimi K3)
8GLM-5.3 (Max)53.54#39 (GLM-5.3)
9GLM-5.3 Flash (Max)45.6#72 (GLM-5.3 Flash)
10DeepSeek V4.1 Flash (Max)36#35 (DeepSeek V4.1 Flash)
11Muse Spark 1.3 (High)33.71#29 (Muse Spark 1.3)

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

Interactive version: theaggregate.ai/benchmark?slug=frontiercs-2-private-set-list-decoding · How It Works · Data refreshed daily, snapshot 2026-10-26.