Meituan · 1.6T (48B active) · 專家混合（MoE）
Frontier-scale agentic and coding MoE with sparse attention and native 1M context 看看你的 GPU 或 Mac 跑不跑得動 LongCat 2.0——最低 894.1 GB，建議 1490.1 GB。
2026-071024K context
| 量化 | 位元 | VRAM | 品質 | 狀態 |
|---|---|---|---|---|
| Q2_K | 2 | 512.7 GB | low | — |
| Q3_K_M | 3 | 717.6 GB | moderate | — |
| Q4_K_M | 4 | 820.1 GB | good | — |
| Q5_K_M | 5 | 1025 GB | good | — |
| Q6_K | 6 | 1229.8 GB | excellent | — |
| Q8_0 | 8 | 1639.6 GB | excellent | — |
| F16 | 16 | 3278.8 GB | lossless | — |
Can I run LongCat 2.0 locally?
- Can I run LongCat 2.0 locally?
- LongCat 2.0 needs about 894.1 GB of memory at a minimum and 1490.1 GB recommended. Open this page to grade it against your GPU or Mac, then run it with runai, Ollama or LM Studio.
- How much VRAM does LongCat 2.0 need?
- At Q4_K_M, LongCat 2.0 uses about 820.1 GB of VRAM. Higher quants need more memory; lower quants fit tighter cards with a quality tradeoff.