RECON (Long-Context Reasoning): leaderboard
RECON (2026) puts a 50K-100K-token criminal, medical or financial case file in context and asks questions that require composing evidence over it, including what changes after a fact is invalidated. Score from -1 to 1 with negative marking for wrong multiple-choice commits; abstaining scores zero; higher is better.
Metric: Score (-1 to 1; mean per-question score over all six tasks; full 50K-100K-token case file in context; 1,414 questions after a closed-book contamination filter; abstention allowed, MCQ-single wrong answers -0.2, MCQ-multiple option-weighted in [-1, 1], ordering by Kendall tau, free-form by two cross-family LLM judges; temperature 0). Source: arxiv.org. Saturation forecast: Around March 2028. 8 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.1 | 0.29 | #229 |
| 2 | Gemini 2.5 Pro | 0.27 | #266 |
| 3 | Kimi K2.5 | 0.26 | #256 |
| 4 | Gemini 2.5 Flash | 0.26 | #453 |
| 5 | GPT-4o Mini (2024-07-18) | 0.23 | #1510 |
| 6 | GPT-4.1 Mini | 0.21 | #779 |
| 7 | Llama 3.3 70B | 0.19 | #1498 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=recon-long-context-reasoning · How It Works · Data refreshed daily, snapshot 2026-11-13.