Qwen2-72B
Parameters
72B
Context Length
33K
Modality
Text
Architecture
Dense
License
Tongyi Qianwen LICENSE AGREEMENT
Release Date
7 Jun 2024
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.90 · Output: $0.90
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
8x RTX 4090
24GB VRAM
Datacenter
3x NVIDIA A100
80GB VRAM
Apple Silicon
2x Apple M3 Max
128GB VRAM
32,768 tokens
Consumer
8x RTX 4090
24GB VRAM
Datacenter
3x NVIDIA A100
80GB VRAM
Apple Silicon
2x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#159
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.644 | 50 |
Graduate-Level QA | 0.424 | 111 |
General Text | 1261 | 147 |
Intelligence Index | 0.06 | 217 |
General Knowledge Reference | 0.823 | 17 |
Rankings
Overall Rank
#159
Coding Rank
-
About Qwen2-72B
Qwen2-72B is Alibaba Cloud's flagship dense foundation model from the Qwen2 generation, optimized for complex reasoning and enterprise-scale NLP. It delivers state-of-the-art coding, mathematics, and multilingual performance.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
128
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
1,000,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
8,192
Number of Layers
80
FFN Intermediate Size (Dense)
29,568
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
152,064
About Qwen2
The Alibaba Qwen2 model family comprises large language models built upon the Transformer architecture. It includes both dense and Mixture-of-Experts (MoE) variants, designed for diverse language tasks. Technical features include Grouped Query Attention and support for extended context lengths up to 131,072 tokens, optimizing memory footprint for inference.