KronLSTM Study - Language - ARC-Easy: leaderboard

KronLSTM (2026): matched research-trained 1.5B models on 100B pretraining tokens, linear and hybrid architectures kept distinct; zero/few-shot downstream task protocol from the paper. Architecture names do not identify unrelated public Mamba, mLSTM or GDN checkpoints. Accuracy (%); higher is better.

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 12 models tracked.

Top models

#ModelScoreOverall rank
1KronLSTM Study KronLSTM 1.5B Linear (100B tokens)74.03
2KronLSTM Study GDN-2 1.5B Hybrid (100B tokens)72.64
3KronLSTM Study Mamba-3 1.5B Hybrid (100B tokens)72.22
4KronLSTM Study KronLSTM 1.5B Hybrid (100B tokens)71.93
5KronLSTM Study KDA 1.5B Linear (100B tokens)71.84
6KronLSTM Study mLSTM 1.5B Linear (100B tokens)71.3
7KronLSTM Study GDN-2 1.5B Linear (100B tokens)71.13
8KronLSTM Study KDA 1.5B Hybrid (100B tokens)71.04
9KronLSTM Study GDN 1.5B Linear (100B tokens)70.54
10KronLSTM Study GDN 1.5B Hybrid (100B tokens)70.54

Interactive version: theaggregate.ai/benchmark?slug=kronlstm-study-language-arc-easy · How It Works · Data refreshed daily, snapshot 2026-10-21.