Qwen · 2026-02 · Dense · Multimodal

Qwen3.5 9B

Qwen3.5 9B is a grouped-query attention (GQA) transformer released by Qwen in 2026-02, with 32 layers, hidden size 4096 and a context window of 262,144 tokens.

Layer stack

Linear ×24 Attention ×8 · Layers 32

Key facts

FamilyQwen
Released2026-02
Params7.9 B
Context262,144 tokens
AttentionGQA (16:4)
Layers32
Hidden4,096
Heads16
Vocab248,320
Positionlearned/absolute
NormRMSNorm
Activationsilu
Dtypebf16
Architecture classQwen3_5ForConditionalGeneration

Architecture overview

Vision input → tokens t₁ t₂ t₃ t₄ input tokens Embedding · Vocab 248,320 → Hidden 4,096 Q1 Q2 Q3 Qn KV1 KV2 KV3 KVn Heads 16 KV heads 4 head dim 256 · learned/absolute FFN · SwiGLU FFN dim 12,288 × 32 transformer block Attention Feed-forward / MoE RMSNorm pre-norm Final norm · RMSNorm LM head → Vocab 248,320 p p p → next token MTP ×1 → +1 future tokens Position learned/absolute Dtype BF16 Context 256K tok Vision ⇢ token
Drawn from the shipped config.json · 32 layers / width 4,096 / context 262,144. Original diagram by this atlas.

Attention

grouped-query attention (GQA) — 16 q-heads / 4 kv-heads.

Feed-forward / MoE

It is a dense model: all 7.9B parameters participate in computing every token.

The configuration ships 1 extra multi-token-prediction (MTP) layers used to accelerate decoding.

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 Qwen3.5 397B A17B
ModelQwen3.5 9BQwen3.5 397B A17BRatio
model_typeqwen3_5qwen3_5_moe
architecturesQwen3_5ForConditionalGenerationQwen3_5MoeForConditionalGeneration
hidden_size40964096≈1
num_hidden_layers3260×0.533
num_attention_heads1632×0.500
num_key_value_heads42×2.00
head_dim256256≈1
intermediate_size12288
hidden_actsilusilu
num_experts_per_tok10
moe_intermediate_size1024
max_position_embeddings262144262144≈1
rms_norm_eps0.0000010.000001≈1
vocab_size248320248320≈1
image_token_id248056248056≈1
tie_word_embeddingsfalsefalse
transformers_version4.57.0.dev04.57.0.dev0
video_token_id248057248057≈1
vision_end_token_id248054248054≈1
vision_start_token_id248053248053≈1
attention_biasfalsefalse
attention_dropout00
attn_output_gatetruetrue
dtypebfloat16bfloat16
eos_token_id248044248044≈1
full_attention_interval44≈1

Most similar architectures

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

Raw config fields

35 fields
architecturesQwen3_5ForConditionalGeneration
image_token_id248056
model_typeqwen3_5
tie_word_embeddingsfalse
transformers_version4.57.0.dev0
video_token_id248057
vision_end_token_id248054
vision_start_token_id248053
attention_biasfalse
attention_dropout0
attn_output_gatetrue
dtypebfloat16
eos_token_id248044
full_attention_interval4
head_dim256
hidden_actsilu
hidden_size4096
initializer_range0.02
intermediate_size12288
layer_typeslinear_attention×24 + full_attention×8
linear_conv_kernel_dim4
linear_key_head_dim128
linear_num_key_heads16
linear_num_value_heads32
linear_value_head_dim128
max_position_embeddings262144
mtp_num_hidden_layers1
mtp_use_dedicated_embeddingsfalse
num_attention_heads16
num_hidden_layers32
num_key_value_heads4
rms_norm_eps0.000001
use_cachetrue
vocab_size248320
mamba_ssm_dtypefloat32