Qwen2.5-7B
Parameters
7B
Context Length
131K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
19 Sept 2024
Knowledge Cutoff
Jun 2024
API Pricing (per 1M)
Self-hosted only
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
131,072 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#188
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.563 | 55 |
Graduate-Level QA | 0.364 | 117 |
Intelligence Index | 0.06 | 236 |
Rankings
Overall Rank
#188
Coding Rank
-
About Qwen2.5-7B
Qwen2.5-7B is a popular open-weights dense model by Alibaba Cloud engineered for advanced reasoning, code synthesis, and structured data extraction. It supports over 29 languages and long-sequence processing up to 131K tokens.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
64
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
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
18,944
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
152,064
About Qwen2.5
Qwen2.5 by Alibaba is a family of dense, decoder-only language models available in various sizes, with some variants utilizing Mixture-of-Experts. These models are pretrained on large-scale datasets, supporting extended context lengths and multilingual communication. The family includes specialized models for coding, mathematics, and multimodal tasks, such as vision and audio processing.