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)→
More from coding & agent
- 250 Builders Hack With Codex at Berlin Community Hackathon Ahead of OpenAI DevDay — paw_lean · 2026-10-26
- Ben Bajarin: Frontier AI is becoming the enterprise cyber-defense stack — BenBajarin · 2026-10-26
- Building AI bots on raw APIs? Devs say models are 'dumb without the harness' — madeofAjala · 2026-10-26
- HarnessMM cuts agent tokens per task by up to 88% while raising success rates — omarsar0 · 2026-10-26
- Microsoft demos intent-classifying agents built with Copilot App and Foundry, deployable across Teams and Outlook — marlene_zw · 2026-10-26
- Looking for a wearable mic with best battery life that feeds recordings to personal agents via MCP — altryne · 2026-10-26