Qwen2.5-3B
Parameters
3B
Context Length
33K
Modality
Text
Architecture
Dense
License
Qwen Research License Agreement
Release Date
19 Sept 2024
Knowledge Cutoff
-
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
32,768 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for Qwen2.5-3B available.
Rankings
Overall Rank
-
Coding Rank
-
About Qwen2.5-3B
Qwen2.5-3B is an efficient dense foundation model developed by Alibaba Cloud balancing compact resource requirements with strong coding and math skills. It offers robust instruction adherence and multilingual fluency over an extensible 128K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
48
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
2,304
Number of Layers
36
FFN Intermediate Size (Dense)
11,008
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
151,936
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.