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Meituan releases LongCat-2.5, a 1.6T multimodal model for agentic coding

By PulseAugur Editorial · [5 sources] ·

Meituan has officially released LongCat-2.5, a native multimodal model boasting 1.6 trillion parameters. This model is designed for long-horizon agentic coding tasks, utilizing approximately 48 billion active parameters per token. Meituan reports significant performance gains on the Terminal Bench v2.1, scoring 88.4, an improvement from its previous 70.8, though open weights are still pending. AI

IMPACT This release advances native multimodal capabilities for complex agentic tasks, potentially improving AI's ability to handle long-horizon coding projects.

RANK_REASON Frontier-lab model release with system card.

Read on Hacker News — AI stories ≥50 points →

AI-generated summary · Google Gemini · from 5 sources. How we write summaries →

Meituan releases LongCat-2.5, a 1.6T multimodal model for agentic coding

How we ranked this

Signal score
7 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Frontier Release
Frontier-lab model release with system card.
Source corroboration
5 independent sources
Strong cross-source corroboration — multiple independent publishers covered this within the clustering window.
Topics
model release, product
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
1 days old
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+1 source(s) since last score
New sources have picked up this story since our last re-score. Score will update on the next scoring pass.

Full methodology in our editorial standards.

COVERAGE [5]

  1. Hacker News — AI stories ≥50 points TIER_1 English(EN) · pretext ·

    LongCat-2.5: Native Multimodality for Agentic Tasks

  2. Pandaily TIER_1 English(EN) · [email protected] (Pandaily) ·

    Meituan Releases LongCat-2.5, a 1.6T Native Multimodal Model Built for Long-Horizon Agentic Coding

    Meituan's LongCat-2.5 is a 1.6T native multimodal model with about 48B active per token, trained with long-horizon RL for agentic coding and optimized for W4A4 inference on domestic compute.

  3. dev.to — LLM tag TIER_1 English(EN) · FreyaLi ·

    Meituan Launches LongCat-2.5, a 1.6-Trillion-Parameter Native Multimodal Model

    <p>Meituan has officially released LongCat-2.5, the latest generation of its native multimodal large model built for long-horizon agent tasks. The model uses a unified token representation for vision and text, activates roughly 48 billion parameters per token out of 1.6 trillion …

  4. Mastodon — mastodon.social TIER_1 English(EN) · CuratedHackerNews ·

    LongCat-2.5: Native Multimodality for Agentic Tasks https:// longcat.ai/blog/longcat-2.5/ # ai

    LongCat-2.5: Native Multimodality for Agentic Tasks https:// longcat.ai/blog/longcat-2.5/ # ai

    LINKS longcat.ai/…/longcat-2.5
  5. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Meituan has released LongCat-2.5, a natively multimodal model with 1.6 trillion parameters, about 48 billion active per token, trained with long-horizon reinfor

    Meituan has released LongCat-2.5, a natively multimodal model with 1.6 trillion parameters, about 48 billion active per token, trained with long-horizon reinforcement learning for agentic coding and optimised for 4-bit inference on domestic chips. Meituan reports 88.4 on Terminal…

    LINKS pandaily.com/meituan-longcat-2-5-official…

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