LongCat 2.0
Active Parameters
1.6T
Context Length
1.05M
Modality
Text
Architecture
Mixture of Experts (MoE)
License
MIT License
Release Date
5 Jul 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.20 · Output: $0.80
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
229x RTX 4090
24GB VRAM
Datacenter
54x NVIDIA A100
80GB VRAM
Apple Silicon
51x Apple M3 Max
128GB VRAM
1,048,756 tokens
Consumer
244x RTX 4090
24GB VRAM
Datacenter
57x NVIDIA A100
80GB VRAM
Apple Silicon
54x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#129
| Benchmark | Score | Rank |
|---|---|---|
Agentic Index | 0.14 | 89 |
Coding Index | 0.45 | 96 |
General Text | 1401 | 118 |
Intelligence Index | 0.19 | 179 |
Rankings
Overall Rank
#129
Coding Rank
#92
About LongCat 2.0
LongCat 2.0 is a large-scale mixture-of-experts model from Meituan that activates 48B parameters out of 1.6T total. It is built for complex repository-level software modifications, extended reasoning, and agentic workflows.
Technical Specifications
Attention
Attention Structure
DeepSeek Sparse Attention
Attention Heads
64
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
1,000,000
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
8,192
Number of Layers
38
FFN Intermediate Size (Dense)
12,288
Multi-Token Prediction Heads
3
Tokenizer
Vocabulary Size
163,840
Mixture of Experts
Total Expert Parameters
48.0B
Number of Experts
768
Active Experts
12
FFN Intermediate Size (per Expert)
2,048
Resources
About LongCat
The LongCat model family developed by Meituan.
Other LongCat Models
- No related models available