TRACK - Multi-Hop QA (Facts in Context): leaderboard

Knowledge-conflict reasoning in TRACK (Testing Reasoning Amid Conflicting Knowledge; Feng et al., EACL 2026): 500 multi-hop questions over Wikidata fact chains, where the needed facts contradict or extend what the model learned in pre-training, answered with the model's own missing facts appended to the prompt. Holistic pass in percent (a correct final answer and reasoning that entails every required fact), higher is better.

Metric: Holistic pass (%; multi-hop questions over Wikidata fact chains, 500 items; the final answer is correct and the reasoning entails every required fact; answered with the model's own missing facts appended to the prompt). Source: arxiv.org. Saturation forecast: Estimated already saturated. 7 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 1.7B83.6#5551
2Qwen 3 4B80.5#2297
3Qwen 3 8B77.7#1838
4GPT-4.1 Mini70.8#775

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=track-multi-hop-qa-facts-in-context · How It Works · Data refreshed daily, snapshot 2026-11-12.