Meituan LongCat-2.0 fully open-sourced under MIT license, releasing 1.6T MoE weights and inference code

美团 LongCat-2.0 完全开源（MIT 许可），1.6T MoE 模型开放权重与推理代码

Meituan fully open-sourced LongCat-2.0 under MIT license, releasing both weights and inference code. It's a 1.6T-parameter MoE model activating ~48B per token, with 1M-token context. LongCat Sparse Attention handles long sequences, Zero-Compute Experts dynamically activate 33B–56B to avoid wasted compute, and MOPD routes tasks across Agent, Reasoning, and Interaction expert groups. On benchmarks: SWE-bench Pro hits 59.5, edging out GPT-5.5's 58.6; Terminal-Bench 2.1 scores 70.8; multilingual SWE-bench reaches 77.3. It natively integrates with Claude Code, OpenClaw, and Hermes Agent, supports GPU and NPU deployment, and has been validated on large-scale domestic clusters.

Why it matters: Meituan fully open-sources LongCat-2.0, a 1.6T MoE model, under MIT license with weights and inference code — a rare move from a major Chinese tech company. The 1M-token context window and sparse attention design are concrete technical hooks, not just marketing. Score held at ...