Hedge-Bench - Competitive Positioning: leaderboard
Metric: Macro dense mean rubric score (out of 4) on the Competitive Positioning task category: each trial scores 0 to 4 by the themes it covers, 4 only with full coverage plus a synthesis that reconciles conflicting evidence, averaged within each task and then over the tasks where the model had a valid run; 102 open-ended financial-analyst research tasks derived from recorded expert analyst discussions, run in the Harbor harness with the Terminus 2 agent over a sandboxed document corpus, eight trials per task, graded by a Gemini-3.1-Pro judge against expert rubric moves with hallucination-supported moves discounted; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 8 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Sonnet 4.6 | 1.95 |
| 2 | Claude Opus 4.7 | 1.74 |
| 3 | Gemini 3.5 Flash | 1.65 |
| 4 | GPT-5.5 | 1.62 |
| 5 | Claude Opus 4.8 | 1.26 |
| 6 | Claude Haiku 4.5 | 1.24 |
| 7 | Gemini 3.1 Pro (Preview) | 0.97 |
| 8 | GPT-5.4 Mini | 0.8 |
Interactive version: theaggregate.ai/benchmark?slug=hedge-bench-competitive-positioning · How It Works · Data refreshed daily, snapshot 2026-09-29.