Qwen · 2026-02 · Sparse MoE · Multimodal

Qwen3.5 35B A3B

Qwen3.5 35B A3B is a grouped-query attention (GQA) transformer released by Qwen in 2026-02, with 40 layers, hidden size 2048 and a context window of 262,144 tokens.

Layer stack

Linear ×30 Attention ×10 · Layers 40

Key facts

FamilyQwen
Released2026-02
Params33.9 B
Active2.7 B
Context262,144 tokens
AttentionGQA (16:2)
Layers40
Hidden2,048
Heads16
Vocab248,320
Positionlearned/absolute
NormRMSNorm
Activationsilu
Dtypebf16
Architecture classQwen3_5MoeForConditionalGeneration

Architecture overview

Vision input → tokens t₁ t₂ t₃ t₄ input tokens Embedding · Vocab 248,320 → Hidden 2,048 Q1 Q2 Q3 Qn KV1 KV2 Heads 16 KV heads 2 head dim 256 · learned/absolute Router E1 E2 E3 E4 E5 E6 E7 E8 +248… Shared expert ×1 top-8 of 256 experts · ≈ 2.7B params active per token × 40 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 · 40 layers / width 2,048 / context 262,144. Original diagram by this atlas.

Attention

grouped-query attention (GQA) — 16 q-heads / 2 kv-heads.

Feed-forward / MoE

It is a sparse mixture-of-experts with 256 routed experts and top-8 routing; about 2.7B parameters are active per 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 27B
ModelQwen3.5 35B A3BQwen3.5 27BRatio
model_typeqwen3_5_moeqwen3_5
architecturesQwen3_5MoeForConditionalGenerationQwen3_5ForConditionalGeneration
hidden_size20485120×0.400
num_hidden_layers4064×0.625
num_attention_heads1624×0.667
num_key_value_heads24×0.500
head_dim256256≈1
intermediate_size17408
hidden_actsilusilu
num_experts_per_tok8
moe_intermediate_size512
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

39 fields
architecturesQwen3_5MoeForConditionalGeneration
image_token_id248056
model_typeqwen3_5_moe
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_size2048
initializer_range0.02
layer_typeslinear_attention×30 + full_attention×10
linear_conv_kernel_dim4
linear_key_head_dim128
linear_num_key_heads16
linear_num_value_heads32
linear_value_head_dim128
max_position_embeddings262144
moe_intermediate_size512
mtp_num_hidden_layers1
mtp_use_dedicated_embeddingsfalse
num_attention_heads16
num_experts256
num_experts_per_tok8
num_hidden_layers40
num_key_value_heads2
rms_norm_eps0.000001
router_aux_loss_coef0.001
shared_expert_intermediate_size512
use_cachetrue
vocab_size248320
mamba_ssm_dtypefloat32