DiNA — 2 Technical Articles

Machine Learning Algorithms & Natural Language Processing

Mar 30, 2026 · Artificial Intelligence

Meituan’s Fully Discrete Multimodal Base (LongCat-Next) Shows All Physical Signals Can Converge to Tokens

LongCat-Next, a 3‑billion‑parameter multimodal model released by Meituan, adopts a pure discrete token‑based architecture (DiNA) and next‑token prediction, outperforming same‑size rivals on OmniDocBench‑EN, CharXivRQ, and matching QwenVL on visual tasks, while avoiding catastrophic forgetting and achieving a SWE‑Bench score of 43.0, as demonstrated through extensive benchmarks, receipt extraction, OCR, audio dialect reasoning, and image generation experiments.

DiNALongCat-NextOmniDocBench

0 likes · 10 min read

Meituan’s Fully Discrete Multimodal Base (LongCat-Next) Shows All Physical Signals Can Converge to Tokens

Machine Learning Algorithms & Natural Language Processing

Mar 28, 2026 · Artificial Intelligence

Do All Physical Signals Reduce to a Single Discrete Token? LongCat‑Next Explained

LongCat‑Next, Meituan’s new 3‑billion‑parameter foundation model, adopts a pure‑discrete DiNA architecture with next‑token prediction, converting vision, audio and text into unified tokens; it surpasses same‑size multimodal models on OmniDocBench‑EN, CharXivRQ and SWE‑Bench, avoids catastrophic forgetting, and introduces dNaViT, RVQ compression and a dual‑path detokenizer for high‑fidelity generation.

DiNALongCat-NextSWE-Bench

0 likes · 10 min read

Do All Physical Signals Reduce to a Single Discrete Token? LongCat‑Next Explained