SciR - Causal Hard: leaderboard
Metric: Accuracy (%) on the 200 hard-tier SciR causal tasks (causal abduction over the Sachs signalling network), rendered as plain natural-language premises (NL); the model reasons with chain-of-thought directly from the task text, temperature 0; answers are checked against the generating formal object; higher is better. Source: arxiv.org. Saturation forecast: Around December 2026. 6 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | DeepSeek R1 | 88.5 |
| 2 | O3 Mini | 85.5 |
| 3 | GPT-4o | 46 |
| 4 | Qwen 3 30B A3B 2507 Instruct | 44.5 |
| 5 | Llama 3.3 70B Instruct | 33 |
| 6 | Olmo 3.1 32B Instruct | 4 |
Interactive version: theaggregate.ai/benchmark?slug=scir-causal-hard · How It Works · Data refreshed daily, snapshot 2026-09-29.