Qwen3-1.7B
Parameters
1.7B
Context Length
33K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
29 Apr 2025
Knowledge Cutoff
Dec 2024
API Pricing (per 1M)
Input: $0.11 · Output: $0.42
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
Rank
#196
| Benchmark | Score | Rank |
|---|---|---|
Intelligence Index | 0.05 | 252 |
Rankings
Overall Rank
#196
Coding Rank
-
About Qwen3-1.7B
Qwen3-1.7B is a high-efficiency dense foundation model from Alibaba Cloud supporting both Thinking and Non-Thinking modes for edge and mobile deployments. It provides low-latency conversational responses and step-by-step logic over an extensible 131K context.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
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
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
2,048
Number of Layers
32
FFN Intermediate Size (Dense)
6,144
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.