Qwen/Qwen1.5-MoE-A2.7B

📊 Model Parameters

Total Parameters 14,315,784,192
Context Length 8,192
Hidden Size 2048
Layers 24
Attention Heads 16
KV Heads 16

💾 Memory Requirements

FP32 (Full) 53.33 GB
FP16 (Half) 26.67 GB
INT8 (Quantized) 13.33 GB
INT4 (Quantized) 6.67 GB

🔑 KV Cache (Inference)

Per Token (FP16) 196.61 KB
Max Context FP32 3.00 GB
Max Context FP16 1.50 GB
Max Context INT8 768.0 MB

⚙️ Model Configuration

Core Architecture

Vocabulary Size151,936
Hidden Size2,048
FFN Intermediate Size5,632
Number of Layers24
Attention Heads16
KV Heads16

Context & Position

Max Context Length8,192
Uses Sliding WindowNo
Sliding Window SizeNot set
Window Attention Layers21
RoPE Base Frequency1000000.0
RoPE ScalingNot set

Attention Configuration

Attention Dropout0%
Attention BiasYes
Tied EmbeddingsNo

Mixture of Experts

MoE Layer Frequency1
Expert FFN Size1,408
Shared Expert FFN Size5,632
Experts per Token4
Number of Experts60
Normalize TopK ProbabilitiesNo

Activation & Normalization

Activation Functionsilu
RMSNorm Epsilon1e-06

Special Tokens

BOS Token ID151,643
Pad Token IDNot set
EOS Token ID151643

Data Type

Model Dtypebfloat16
Layer Types:
Attention
MLP/FFN
Normalization
Embedding