Qwen3-8B
Parameters
8B
Context Length
131K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
29 Apr 2025
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.18 · Output: $2.10
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
#176
| Benchmark | Score | Rank |
|---|---|---|
Agentic Index | 0.02 | 105 |
Coding Index | auto 0.09 | 142 |
Intelligence Index | auto 0.03 Standard 1 | 231 249 |
Rankings
Overall Rank
#176
Coding Rank
#125
About Qwen3-8B
Qwen3-8B is an open-weights causal language model from Alibaba Cloud combining deliberative chain-of-thought reasoning with rapid conversational inference. Trained on 36T tokens across 119 languages, it natively integrates with external agent tooling.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
64
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
4,096
Number of Layers
40
FFN Intermediate Size (Dense)
12,288
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.