body { background: #06080c; color: #e5e9f0; margin: 0; } .rw-nojs-bar { max-width: 880px; margin: 0 auto; padding: 18px 16px 14px; } .rw-nojs-bar .rw-nojs-brand { font: 700 20px/1 Inter, system-ui, sans-serif; color: #e5e9f0; text-decoration: none; } .rw-nojs-nav { max-width: 880px; margin: 0 auto; padding: 0 16px 14px; border-bottom: 1px solid #1c2230; font: 500 14px/1.4 Inter, system-ui, sans-serif; } .rw-nojs-nav a { color: #6f9bff; margin: 0 14px 6px 0; text-decoration: none; display: inline-block; } .rw-nojs-nav a:hover { text-decoration: underline; } .rw-nojs-note { max-width: 880px; margin: 12px auto 0; padding: 0 16px; font: 400 13px/1.5 Inter, system-ui, sans-serif; color: #8a93a6; } #root [data-rw-crawler] { max-width: 880px; margin: 0 auto; padding: 8px 16px 48px; font: 400 16px/1.65 Inter, system-ui, sans-serif; color: #e5e9f0; } #root [data-rw-crawler] a { color: #6f9bff; } #root [data-rw-crawler] h1 { font-size: 28px; line-height: 1.2; } #root [data-rw-crawler] h2 { font-size: 20px; margin-top: 28px; } #root [data-rw-crawler] img { max-width: 100%; height: auto; } #root [data-rw-crawler] ul { padding-left: 0; list-style: none; } #root [data-rw-crawler] li { margin: 0 0 18px; } #root [data-rw-crawler] .rw-pagination { margin: 28px 0 0; display: flex; flex-wrap: wrap; gap: 12px; align-items: baseline; } #root [data-rw-crawler] .rw-pagination strong { color: #e5e9f0; } .rw-nojs-footer { max-width: 880px; margin: 40px auto 0; padding: 22px 16px 44px; border-top: 1px solid #1c2230; font: 400 13px/1.6 Inter, system-ui, sans-serif; color: #8a93a6; } .rw-nojs-footer .rw-nojs-fcols { display: flex; flex-wrap: wrap; gap: 28px 40px; margin-bottom: 20px; } .rw-nojs-footer h2 { font-size: 11px; letter-spacing: 0.05em; text-transform: uppercase; color: #b7c0d3; margin: 0 0 8px; } .rw-nojs-footer a { color: #6f9bff; text-decoration: none; display: block; margin: 0 0 5px; } .rw-nojs-footer a:hover { text-decoration: underline; } .rw-nojs-footer .rw-nojs-legal { font: 400 12px/1.6 Inter, system-ui, sans-serif; color: #6b7384; margin: 0; } .rw-nojs-footer .rw-nojs-legal a { display: inline; } RuntimeWire AI Startups Venture Products Funding Exits Models Head-to-Head About You're browsing RuntimeWire with JavaScript disabled. Articles and navigation work fully. Interactive features — search, comments, and newsletter signup — require JavaScript.

meituan

Meituan: LongCat 2.0

meituan/longcat-2.0

LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total.

Context window: 1,048,756 tokens
Input: text
Output: text
Pricing: $0.3/M input tokens, $1.2/M output tokens

View on OpenRouter. Model data sourced from OpenRouter.

Sections

AI Startups Venture Products Funding Exits

Publication

About FAQ Contact Editorial Policy Corrections Policy Ethics

Tools

AI Model Pricing Head-to-Head SynthID Remover

Legal

Privacy Terms

© 2026 RuntimeWire, Inc. All rights reserved. · Gradient Noise, Inc.
An independent startup and technology publication based in Austin, Texas and San Francisco, California. Send tips to tips@runtimewire.com.