FrontierCS 2 - Graph Mining Method Selection: 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 Superseded attempts are not selected by score.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 January 2027. 14 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 5.5 (Max)91.95#5 (Claude Opus 5.5)
2GPT-6.1 Sol (xHigh)91.07#7 (GPT-6.1 Sol)
3Gemini 4 Argon (High)91.04#8 (Gemini 4 Argon)
4DeepSeek V4.1 Flash (1017)90.98#27
5GPT-6 Astra (xHigh)90.81#6 (GPT-6 Astra)
6GLM-5.3 (Max)87.97#39 (GLM-5.3)
7Muse Wonder (Max)85.13#15 (Muse Wonder)
8DeepSeek V4.1 Flash (Max)83.84#35 (DeepSeek V4.1 Flash)
9Kimi K3 (High)83.54#33 (Kimi K3)
10GLM-5.3 Flash (Max)83.5#72 (GLM-5.3 Flash)
11Muse Spark 1.3 (High)62.44#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-graph-mining-method-selection · How It Works · Data refreshed daily, snapshot 2026-10-26.