FrontierCS 2 - Fixed-Length Clustered Sparse Multiplication: 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 Superseded attempts are not selected by score.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 September 2027. 14 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 5.5 (Max)66.87#5 (Claude Opus 5.5)
2GPT-6 Astra (xHigh)65.47#6 (GPT-6 Astra)
3GPT-6.1 Sol (xHigh)64.41#7 (GPT-6.1 Sol)
4Gemini 4 Argon (High)64.35#8 (Gemini 4 Argon)
5DeepSeek V4.1 Flash (Max)64.12#35 (DeepSeek V4.1 Flash)
6DeepSeek V4.1 Flash (1017)63.31#27
7Muse Wonder (Max)62.84#15 (Muse Wonder)
8GLM-5.3 (Max)62.47#39 (GLM-5.3)
9Muse Spark 1.3 (High)62.18#29 (Muse Spark 1.3)
10Kimi K3 (High)56.68#33 (Kimi K3)
11GLM-5.3 Flash (Max)0#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-fixed-length-clustered-sparse-multiplication · How It Works · Data refreshed daily, snapshot 2026-10-26.