supermarket

Benchmarks

Long context

Finding, tracking and reasoning over information spread across very long inputs (100K to 1M+ tokens).

See the ranking

How the score works

A model's score is built only from results that someone other than its maker ran.

  • The scoring set is the benchmarks chosen for this specialty. A benchmark takes part only when at least 5 models have an independent or third-party result on it.
  • Each result is rescaled to 0 to 1, and a model's best setting counts.
  • The score is the average over the benchmarks a model has, times 100.
  • A model ranks only when it has results on enough of them. The rest show "Not enough independent results yet".
  • Self-reported results are shown but never counted.

Method: category-2026-09-29.1

Scoring set and effective set

Scoring set: AA-LCR (Artificial Analysis Long Context Reasoning).

Effective set (used for the score today): none yet.

All benchmarks