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ไทย(TH) LongCat-2.5 โมเดล AI 1.6 ล้านล้านพารามิเตอร์ ฝึกบนชิปจีนล้วนได้อย่างไร?

Meituan's LongCat-2.5: 1.6T parameters trained on Chinese chips

By PulseAugur Editorial · [1 sources] ·

Meituan has unveiled LongCat-2.5, a 1.6 trillion parameter AI model trained entirely on Chinese-manufactured chips with limited memory per card. The model utilizes a novel distributed training architecture to manage its massive parameter count across numerous GPUs, employing techniques like parameter splitting and expert parallelism within supernodes. LongCat-2.5 also incorporates 4-bit precision for weights and activations, significantly boosting inference speed and reducing computational load, with reported performance competitive with models like Claude Opus 4.8 and 5. AI

IMPACT Demonstrates advanced distributed training techniques on constrained hardware, potentially enabling larger models in regions with limited access to high-end GPUs.

RANK_REASON Frontier-lab model release with system card and technical details. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Meituan's LongCat-2.5: 1.6T parameters trained on Chinese chips

How we ranked this

Signal score
83 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
Frontier-lab model release with system card and technical details. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, infra
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High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 ไทย(TH) · Nokka ·

    LongCat-2.5: How a 1.6 Trillion Parameter AI Model Was Trained Entirely on Chinese Chips?

    <p><em>โดย Nokka (นก-กา) | 4 พ.ย. 2026</em></p> <p><a class="article-body-image-wrapper" href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2F04z6…

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