gwBenchmarks: leaderboard
Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast waveform surrogates from expensive numerical relativity simulations, modeling orbital dynamics of black holes, fitting merger remnant properties and constructing template banks. These problems demand extreme precision to support detection and parameter inference,
Metric: Waveform (self-reported). Source: benchmarklist.com. Saturation forecast: Around January 2027. 12 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.6 | 14.22 | #90 |
| 2 | Claude Opus 4.6 | 14.75 | #63 |
| 3 | Claude Opus 4.7 | 16.48 | #49 |
| 4 | GPT-5.5 (High) | 17.82 | #31 (GPT-5.5) |
| 5 | GPT-5.3 Codex | 17.82 | #69 |
| 6 | GPT-5.2 | 19.35 | #110 |
| 7 | Gemini 3 Flash | 21.27 | #99 |
| 8 | Gemini 3.1 Pro (Preview) | 34.25 | #58 |
| 9 | GPT-5.4 Mini | 35.97 | #212 |
| 10 | Kimi K2.6 | 39.12 | #104 |
| 11 | DeepSeek V4 Pro | 48.3 | #102 |
| 12 | Claude Haiku 4.5 | 59.31 | #280 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=gwbenchmarks · How It Works · Data refreshed daily, snapshot 2026-10-20.