Qwen/Qwen3-235B-A22B

📊 Model Parameters

Total Parameters 235,093,634,560
Context Length 40,960
Hidden Size 4096
Layers 94
Attention Heads 64
KV Heads 4

💾 Memory Requirements

FP32 (Full) 875.79 GB
FP16 (Half) 437.90 GB
INT8 (Quantized) 218.95 GB
INT4 (Quantized) 109.47 GB

🔑 KV Cache (Inference)

Per Token (FP16) 192.51 KB
Max Context FP32 14.69 GB
Max Context FP16 7.34 GB
Max Context INT8 3.67 GB

⚙️ Model Configuration

Core Architecture

Vocabulary Size151,936
Hidden Size4,096
FFN Intermediate Size12,288
Number of Layers94
Attention Heads64
KV Heads4
Head Dimension128

Context & Position

Max Context Length40,960
Uses Sliding WindowNo
Sliding Window SizeNot set
RoPE Base Frequency1000000.0
RoPE ScalingNot set
Window Attention Layers94

Attention Configuration

Attention BiasNo
Attention Dropout0%
Tied EmbeddingsNo

Mixture of Experts

MoE Layer Frequency1
Expert FFN Size1,536
Experts per Token8
Number of Experts128
Normalize TopK ProbabilitiesYes

Activation & Normalization

Activation Functionsilu
RMSNorm Epsilon1e-06

Special Tokens

BOS Token ID151,643
Pad Token IDNot set
EOS Token ID151645

Data Type

Model Dtypebfloat16
Layer Types:
Attention
MLP/FFN
Normalization
Embedding