Qwen3-30B-A3B
Active Parameters
30B
Context Length
131K
Modality
Text
Architecture
Mixture of Experts
KV Cache Rate
240 KB/tok
License
Apache 2.0
Release Date
29 Apr 2025
Knowledge Cutoff
Mar 2025
API Pricing (per 1M)
Input: $0.10 · Output: $0.30
Hardware Sizing
Precision
Context
Workload Memory: 19.74 GB
INT4 · 8K context
Base Weights: 15.37 GB
KV Cache: 1.88 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
19.7 / 21.6 GB usable
2x RTX 4090 24GB
19.7 / 43.2 GB usable · TP 2
Apple M3 Pro 36GB
19.7 / 27.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Architecture Diagram
Evaluation Benchmarks
Rank
#154
| Benchmark | Score | Rank |
|---|---|---|
Software Engineering | 0.60 | 26 |
Graduate-Level QA | 0.658 | 91 |
Agentic Index | auto 0.9 | 118 |
General Text | 1382 | 128 |
Coding Index | 0.12 | 144 |
Intelligence Index | auto 0.08 Standard 0.07 | 265 285 |
Rankings
Overall Rank
#154
Coding Rank
#119
About Qwen3-30B-A3B
Qwen3-30B-A3B is an efficient Mixture-of-Experts model from Alibaba Cloud activating 3.3B parameters per token for high-throughput reasoning. It features dual thinking modes and multilingual fluency across 119 languages over a 131K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
96
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
1,000,000
Normalization
Layer Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
60
FFN Intermediate Size (Dense)
768
Tokenizer
Vocabulary Size
151,936
Mixture of Experts
Total Expert Parameters
3.0B
Number of Experts
128
Active Experts
8
FFN Intermediate Size (per Expert)
768
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.