Qwen · 2025-04 · Dense

Qwen3 0.6B

Qwen3 0.6B is a grouped-query attention (GQA) transformer released by Qwen in 2025-04, with 28 layers, hidden size 1024 and a context window of 40,960 tokens.

Layer stack

Attention ×28 · Layers 28

Key facts

FamilyQwen
Released2025-04
Params0.6 B
Context40,960 tokens
AttentionGQA (16:8)
Layers28
Hidden1,024
Heads16
Vocab151,936
PositionRoPE
NormRMSNorm
Activationsilu
Dtypebf16
Architecture classQwen3ForCausalLM

Architecture overview

t₁ t₂ t₃ t₄ input tokens Embedding · Vocab 151,936 → Hidden 1,024 Q1 Q2 Q3 Qn KV1 KV2 KV3 KVn Heads 16 KV heads 8 head dim 128 · RoPE FFN · SwiGLU FFN dim 3,072 × 28 transformer block Attention Feed-forward / MoE RMSNorm pre-norm Final norm · RMSNorm LM head → Vocab 151,936 p p p → next token Position RoPE Dtype BF16 Context 40K tok
Drawn from the shipped config.json · 28 layers / width 1,024 / context 40,960. Original diagram by this atlas.

Attention

grouped-query attention (GQA) — 16 q-heads / 8 kv-heads. RoPE θ=1,000,000.

Feed-forward / MoE

It is a dense model: all 0.6B parameters participate in computing every token.

Field-level comparison

Compared against the previous model of the same lab; where none exists, against the structurally closest model. The ratio column is this model divided by the comparison model.

Full-field comparison vs predecessor Qwen2.5 7B
ModelQwen3 0.6BQwen2.5 7BRatio
model_typeqwen3qwen2
architecturesQwen3ForCausalLMQwen2ForCausalLM
hidden_size10243584×0.286
num_hidden_layers2828≈1
num_attention_heads1628×0.571
num_key_value_heads84×2.00
head_dim128
intermediate_size307218944×0.162
hidden_actsilusilu
rope_theta10000001000000≈1
max_position_embeddings4096032768×1.25
sliding_window131072
rms_norm_eps0.0000010.000001≈1
vocab_size151936152064≈1
torch_dtypebfloat16bfloat16
attention_biasfalse
attention_dropout00
bos_token_id151643151643≈1
eos_token_id151645151645≈1
initializer_range0.020.02≈1
max_window_layers2828≈1
tie_word_embeddingstruefalse
transformers_version4.51.04.43.1
use_cachetruetrue
use_sliding_windowfalsefalse

Most similar architectures

Similarity values range from 0 (no shared categorical features) to 1 (identical profiles).

Raw config fields

24 fields
architecturesQwen3ForCausalLM
attention_biasfalse
attention_dropout0
bos_token_id151643
eos_token_id151645
head_dim128
hidden_actsilu
hidden_size1024
initializer_range0.02
intermediate_size3072
max_position_embeddings40960
max_window_layers28
model_typeqwen3
num_attention_heads16
num_hidden_layers28
num_key_value_heads8
rms_norm_eps0.000001
rope_theta1000000
tie_word_embeddingstrue
torch_dtypebfloat16
transformers_version4.51.0
use_cachetrue
use_sliding_windowfalse
vocab_size151936