Meituan Launches LongCat-2.0 Using Chinese Computing Hardware
美團推出 LongCat-2.0，全面採用中國計算硬體
Introduction
Meituan has introduced LongCat-2.0, a large language model that was developed using only Chinese hardware for both its training and its operation.
美團推出了 LongCat-2.0，這是一個大語言模型，在其訓練與運行過程中完全使用中國硬體開發。
Main Body
LongCat-2.0 marks a major change in how AI is developed in China. The model features 1.6 trillion parameters and can process a huge amount of data at once. Unlike earlier versions of Chinese AI, which often used foreign hardware for training, LongCat-2.0 was trained on a massive network of 50,000 domestic accelerators. To make this possible, Meituan used specialized super-computers and Huawei's communication software to help the chips work together efficiently.
LongCat-2.0 標誌著中國 AI 開發方式的一個重大轉變。該模型擁有 1.6 兆個參數，能一次處理海量數據。與早期經常使用國外硬體進行訓練的中國 AI 不同，LongCat-2.0 是在一個由 5 萬個國產加速器組成的龐大網絡上訓練而成。為了實現這一目標，美團使用了專用的超級電腦和華為的通信軟體，以協助晶片高效協作。
In terms of performance, the model is as capable as Google's Gemini 3.1 Pro and actually performs better in some specific technical tests. However, it still struggles with complex reasoning when compared to top systems like GPT-5.5. Meituan emphasized that while the hardware works, the domestic software is not yet as advanced as NVIDIA's tools. Furthermore, the company noted that limited memory on each device was a primary problem during the training process.
在性能方面，該模型的能力與 Google 的 Gemini 3.1 Pro 相當，甚至在某些特定的技術測試中表現更佳。然而，與 GPT-5.5 等頂尖系統相比，它在處理複雜推理時仍顯吃力。美團強調，雖然硬體可行，但國產軟體尚未達到 NVIDIA 工具的先進程度。此外，公司指出，每個設備的記憶體限制是訓練過程中的主要問題。
This achievement is strategically important because of US export restrictions on high-end chips. By successfully building a massive model on local hardware, Meituan has shown that China is becoming less dependent on restricted technology. Consequently, Meituan is investing more in local semiconductor companies like MetaX and Moore Threads to ensure they have a reliable, independent supply of computing power.
由於美國對高端晶片實施出口限制，這項成就具有重要的戰略意義。美團成功在本地硬體上構建大規模模型，證明了中國對受限技術的依賴程度正在降低。因此，美團正加大對 MetaX 和摩爾线程 (Moore Threads) 等本地半導體公司的投資，以確保擁有可靠且獨立的算力供應。
Conclusion
LongCat-2.0 proves that it is possible to train world-class AI on Chinese hardware, even though software and memory issues still need to be solved.
LongCat-2.0 證明了即便軟體與記憶體問題仍待解決，使用中國硬體訓練出世界級 AI 仍是可行的。
Vocabulary Learning
The 'Contrast Shift': Moving from A2 to B2
At the A2 level, you probably use 'but' for everything. To reach B2, you need to express how things are different using more sophisticated logical connectors.
Look at these two sentences from the text:
- "The model is as capable as Gemini... However, it still struggles with complex reasoning."
- "...even though software and memory issues still need to be solved."
The B2 Upgrade Path:
Instead of saying: "The hardware is good but the software is bad" (A2), try these structures:
-
The 'However' Pivot: Use this to start a new sentence. It creates a formal pause that tells the reader a contradiction is coming.
- Example: "The chips are fast. However, the memory is limited."
-
The 'Even Though' Bridge: Use this to connect two opposite ideas in one sentence. It shows that one fact does not stop the other from being true.
- Example: "Even though they lack NVIDIA tools, they built a great model."
Quick Vocabulary Bridge
To sound more like a B2 speaker, replace basic verbs with 'Precision Verbs' found in the article:
| A2 Word | B2 Precision Word | Why it's better |
|---|---|---|
| Show | Emphasize | It means to show something with strength |
| Help | Ensure | It means to make sure something will happen |
| Use | Process | Specifically used for data and information |