China’s NEW Meituan LongCat 2.0 Tested!

The video discusses Long Cat 2.0, a newly released open-source AI model from China that serves as the full model behind the previously available Owl Alpha API. The model features Long Cat sparse attention and mixture of experts architecture. On benchmarks like Terminal Bench 2.1, it holds its own against other models, though Opus 4.8 significantly outperforms it. A notable aspect is that Long Cat was trained on Meituan's proprietary chip without using any Nvidia hardware—Meituan being China's equivalent to DoorDash, highlighting how major non-tech companies are now developing their own AI models.

The presenter tested Long Cat's practical capabilities by creating various games including Dragon Realm, Skyrim-style games, and other interactive applications. The results were mixed, with graphics and functionality being basic and buggy compared to alternatives. On benchmark evaluations, Long Cat slightly underperforms GPT-4.5, though it outperforms it on SWE-bench Pro. However, the most relevant comparison is against GLM-5.2, another recent Chinese open-source model.

Side-by-side testing against GLM-5.2 showed consistent advantages for GLM-5.2 across multiple game generation tasks: the Crib game, Dragon Ball game, Skyrim implementation, and Voxel Craft all performed notably better with GLM-5.2, featuring better graphics, fewer bugs, and more interesting gameplay mechanics. The presenter concludes that while Long Cat is interesting as an emerging model, GLM-5.2 remains the superior choice for open-source applications and practical use cases.