Open-Source LongCat-2.0 Matches GPT-5.5 in Coding Tasks
rohanpaul_ai · x · 2026-07-08
Open-sourced by Meituan, LongCat-2.0 is a MoE model with approximately 1.6T parameters. In local agent tests conducted via the @kilocode CLI on atomic.chat, LongCat-2.0 performed similarly to GPT-5.5 on a "Duck Hunt" game coding task. The local run consumed about 70.3K tokens at $0 cost, while the cloud-based GPT-5.5 consumed 64.9K tokens costing $0.65. Rather than directly answering prompts, the task required the agent to actually build and iteratively modify code. LongCat reportedly handled the logic for ducks, waves, ammo, hit physics, falling animations, and the dog retrieval loop quite well, demonstrating competitive performance in a three-round iterative agent workflow.
Related event: Meituan Open-Sources LongCat-2.0, a Trillion-Parameter MoE Model(2 posts)→
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