# LongCat-2.5 — Meituan opens weights of its 1.6T agentic model

> Meituan's LongCat-2.5 puts a 1.6T multimodal agent model on Hugging Face under the MIT license.

- Org: Meituan
- Date: 2026-11-10
- Category: model
- Source: https://huggingface.co/meituan-longcat/LongCat-2.5
- Canonical page: https://ai-tldr.dev/releases/meituan-longcat-2-5/

## In short

Meituan released the weights of LongCat-2.5 under the MIT license. It is a 1.6T-parameter multimodal mixture-of-experts model with about 48B active per token, built for long-horizon agent tasks.

## What it is

LongCat-2.5 is Meituan's native multimodal mixture-of-experts model for long-horizon agentic tasks. The weights are now on Hugging Face under the MIT license, after Meituan unveiled the model on November 1. It succeeds LongCat-2.0.

## How it works

The model has 1.6 trillion total parameters and about 48 billion active per token, with hybrid thinking and non-thinking modes. The model card says the expert weights are quantized to W4A4.

## Why it matters

Open weights at this size with a permissive license give teams a self-hostable agent model that Meituan's own benchmarks place close to closed frontier models. The scores are self-reported, so independent tests still need to confirm them.

## Who it's for

agent builders, teams that self-host large models

## Try it

https://huggingface.co/meituan-longcat/LongCat-2.5

## Quick facts

- Maker: Meituan (LongCat team)
- License: MIT (weights)
- Size: 1.6T total, ~48B active per token
- Modes: Hybrid thinking and non-thinking
- Terminal Bench v2.1: 88.4 (self-reported)
- Availability: Hugging Face weights, longcat.ai chat

## FAQ

### Is LongCat-2.5 open source and free for commercial use?

LongCat-2.5 weights are published on Hugging Face under the MIT license, which allows commercial use and fine-tuning. The model card adds that the license does not grant rights to Meituan trademarks or patents. Teams should read the LICENSE file in the repository before shipping a product.

### How does LongCat-2.5 compare with Claude Opus 5 and GPT-5.6-Sol?

On Terminal Bench v2.1, Meituan's model card reports 88.4 for LongCat-2.5, against 89.1 for Claude-Opus-5 and 88.8 for GPT-5.6-Sol. Many LongCat scores are in-house measurements, and the card says they are indicative only. No independent evaluation was found.

### What is new compared with LongCat-2.0?

LongCat-2.5 is the successor to LongCat-2.0 and is a native multimodal model with hybrid thinking and non-thinking modes. It keeps the 1.6T-parameter mixture-of-experts layout with about 48B active parameters per token. The model card lists the expert weights as quantized to W4A4.

### Where can LongCat-2.5 run?

The LongCat-2.5 model card points to an NPU deployment guide built on SGLang-FluentLLM. No Hugging Face inference provider hosted the model at the time of checking. A chat interface at longcat.ai lets people try it without downloading weights.

## Links

- [Hugging Face Model](https://huggingface.co/meituan-longcat/LongCat-2.5)
- [Tech Blog](https://longcat.ai/blog/longcat-2.5/)
- [License](https://huggingface.co/meituan-longcat/LongCat-2.5/blob/main/LICENSE)
- [NPU Deployment Guide](https://github.com/meituan-longcat/SGLang-FluentLLM/blob/longcat-2.5-npu/npu_test/ReadMe.md)