LongCat 2.0 (Open Source) Tested: Benchmarks, Games, and GLM 5.2 Comparison
The episode covers the official release of LongCat 2.0, an open-source Chinese agentic model revealed as the model behind the AoAlpha free API, with features like Sparse Attention, Zero Compute Experts, and MIPD. The host reviews benchmark claims (including Terminal Bench 2.1 and SWE-Bench Pro comparisons versus GPT-5.5 and Opus 4.8) and shares hands-on tests building game demos such as Dragon Realm, a Skyrim-style open world, and VoxelCraft, noting mixed results and frequent bugs. Access issues are mentioned, including difficulty using the API without a Chinese setup, so the model is tested via the website chat. A key point is that LongCat was trained on China’s Meituan chips without NVIDIA. Overall, GLM 5.2 is judged stronger in side-by-side game benchmarks, and the host promotes the AI Profit Boardroom and Agent OS setup.
00:00 LongCat 2.0 Launch
00:36 Benchmarks and API Hurdles
01:38 Game Demos Dragon Realm
02:23 Goldy Bench Verdict
02:43 Trained Without NVIDIA
03:32 How to Use It
03:51 Eval Results vs GPT
04:17 GLM 5.2 Showdown
06:13 Final Take and Recommendation
06:35 Agent OS and Boardroom Plug
07:37 Wrap Up