Meituan Trains 1.6T LongCat-2.0 End-to-End on Chinese Chips

A Chinese food delivery company just trained a 1.6-trillion-parameter language model without touching an Nvidia chip. The South China Morning Post reported on June 30 that Meituan released LongCat-2.0, a model with a 1-million-token context window, trained end-to-end on large clusters of domestic AI ASIC superpods. The bit worth dwelling on is 'end-to-end', meaning both pre-training and inference ran on home-grown silicon.

That distinction matters because the previous Chinese frontier benchmark, DeepSeek's V4-pro from April 2026, used domestic chips only for the lighter inference step. Pre-training is the computationally intensive part, the part where you stream huge volumes of tokens through tens of thousands of accelerators and need the cluster interconnect not to drop. To make that work without Nvidia's NCCL, Meituan integrated Huawei's Collective Communication Library, the chip-to-chip plumbing that keeps a training run stable at scale.

According to SCMP, LongCat-2.0 lands on par with DeepSeek V4-pro on benchmarks. Take that as Meituan's claim rather than settled fact, since there is no independent leaderboard run yet and the article does not break out which evals it is referring to. The honest caveat is that 'on par' headlines have a long history of softening under closer inspection, and a vendor announcement is not a third-party eval.

What the reporting does not give you is the harder economic question: how wall-clock time, accelerator count and energy bill compared to an equivalent Nvidia run. SCMP cites tens of thousands of ASICs in the cluster but does not put a number on cost or duration, and it does not name which domestic chip line did the work, which is the detail that would tell you whether this generalises to other labs.

The forward-looking read is straightforward. If a non-AI-native company like Meituan can complete a trillion-parameter training run on domestic silicon, the export-controls story changes shape. The question stops being whether China can serve frontier models locally, and starts being how quickly Huawei's training stack becomes the default for everyone else inside the firewall.