Qwen3-14B
Parameters
14B
Context Length
131K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
29 Apr 2025
Knowledge Cutoff
Jan 2025
API Pricing (per 1M)
Input: $0.35 · Output: $4.20
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
131,072 tokens
Consumer
3x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#174
| Benchmark | Score | Rank |
|---|---|---|
Agentic Index | 0.02 | 107 |
Coding Index | 0.14 | 136 |
Intelligence Index | 0.01 | 208 |
Rankings
Overall Rank
#174
Coding Rank
#123
About Qwen3-14B
Qwen3-14B is a dense foundation model by Alibaba Cloud optimized for multi-step reasoning, mathematical problem solving, and MCP-compatible agent workflows. It features togglable thinking modes and an extensible 131K token context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
80
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
1,000,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
Layer Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
5,120
Number of Layers
48
FFN Intermediate Size (Dense)
17,408
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
151,936
About Qwen 3
The Alibaba Qwen 3 model family comprises dense and Mixture-of-Experts (MoE) architectures, with parameter counts from 0.6B to 235B. Key innovations include a hybrid reasoning system, offering 'thinking' and 'non-thinking' modes for adaptive processing, and support for extensive context windows, enhancing efficiency and scalability.