FrontierCS 2 - Hypergraph Core Numbers: 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 Superseded attempts are not selected by score.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 2028. 14 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek V4.1 Flash (1017)59.07#27
2Gemini 4 Argon (High)58.88#8 (Gemini 4 Argon)
3DeepSeek V4.1 Flash (Max)58.23#35 (DeepSeek V4.1 Flash)
4Muse Wonder (Max)57.62#15 (Muse Wonder)
5GPT-6 Astra (xHigh)52.18#6 (GPT-6 Astra)
6Claude Opus 5.5 (Max)49.68#5 (Claude Opus 5.5)
7GPT-6.1 Sol (xHigh)47.12#7 (GPT-6.1 Sol)
8Kimi K3 (High)43.83#33 (Kimi K3)
9GLM-5.3 (Max)43.1#39 (GLM-5.3)
10GLM-5.3 Flash (Max)0#72 (GLM-5.3 Flash)
11Muse Spark 1.3 (High)0#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-hypergraph-core-numbers · How It Works · Data refreshed daily, snapshot 2026-10-26.