GLM · 2026-08 · Sparse MoE · Multimodal

GLM-5.3-Flash

GLM-5.3-Flash is a multi-head latent attention (MLA) transformer released by GLM in 2026-08, with 45 layers, hidden size 4096 and a context window of 1,048,576 tokens.

Layer stack

Linear ×34 sparse ×11 · Layers 45

Key facts

FamilyGLM
Released2026-08
Params328.9 B
Active13 B
Context1,048,576 tokens
AttentionMLA · kv_lora_rank 512
Layers45
Hidden4,096
Heads64
Vocab154,880
Positionlearned/absolute
NormRMSNorm
Activationsilu
Dtypefp8
Architecture classGlm5NextForConditionalGeneration

Architecture overview

Vision input → tokens t₁ t₂ t₃ t₄ input tokens Embedding · Vocab 154,880 → Hidden 4,096 Q · 64 Wᴰᴷⱽ ↓ c_KV · 512 kᴿ · RoPE 0 Wᵁᴷ/Wᵁⱽ ↑ ⊕kᴿ Attention KV cache/token ≈ 512 vs dense 2·4,096 → ≈ 1/16.0 Router E1 E2 E3 E4 E5 E6 E7 E8 +280… Shared expert ×1 top-8 of 288 experts · ≈ 13B params active per token × 45 transformer block Attention Feed-forward / MoE RMSNorm pre-norm Final norm · RMSNorm LM head → Vocab 154,880 p p p → next token MTP ×1 → +1 future tokens Position learned/absolute Dtype FP8 Context 1024K tok Vision ⇢ token
Drawn from the shipped config.json · 45 layers / width 4,096 / context 1,048,576. Original diagram by this atlas.

Attention

multi-head latent attention (MLA). kv_lora_rank=512.

Feed-forward / MoE

It is a sparse mixture-of-experts with 288 routed experts and top-8 routing; about 13B 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 GLM-5.3
ModelGLM-5.3-FlashGLM-5.3Ratio
model_typeglm5_nextglm_moe_dsa
architecturesGlm5NextForConditionalGenerationGlmMoeDsaForCausalLM
hidden_size40966144×0.667
num_hidden_layers4578×0.577
num_attention_heads6464≈1
num_key_value_heads6464≈1
head_dim0192×0.000
intermediate_size1228812288≈1
hidden_actsilusilu
n_routed_experts288256×1.13
num_experts_per_tok88≈1
n_shared_experts11≈1
moe_intermediate_size20482048≈1
kv_lora_rank512512≈1
qk_rope_head_dim064×0.000
q_lora_rank15362048×0.750
max_position_embeddings10485761048576≈1
rms_norm_eps0.000010.00001≈1
vocab_size154880154880≈1
num_nextn_predict_layers11≈1
image_token_id154854
video_token_id154855
image_start_token_id154830
image_end_token_id154831
video_start_token_id154832
video_end_token_id154833

Most similar architectures

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

Raw config fields

65 fields
architecturesGlm5NextForConditionalGeneration
image_token_id154854
video_token_id154855
image_start_token_id154830
image_end_token_id154831
video_start_token_id154832
video_end_token_id154833
tie_word_embeddingsfalse
model_typeglm5_next
transformers_version5.16.0
attention_biasfalse
attention_dropout0
dtypebfloat16
eos_token_id154820×1 + 154827×1 + 154829×1
first_k_dense_replace3
hc_eps0.000001
hc_mult4
hc_sinkhorn_iters20
head_dim0
hidden_actsilu
hidden_size4096
index_head_dim128
index_kpool4
index_kpool_always_select_tailtrue
index_kpool_compresstrue
index_n_heads32
index_topk2048
index_share_for_mtp_iterationtrue
indexer_rope_interleavetrue
indexer_typesfull×45
initializer_range0.02
intermediate_size12288
kv_lora_rank512
layer_typeslinear_attention×34 + deepseek_sparse_attention×11
max_position_embeddings1048576
mhctrue
mla_use_nopetrue
mlp_layer_typesdense×3 + sparse×42
moe_intermediate_size2048
moe_router_dtypefloat32
n_group1
n_routed_experts288
n_shared_experts1
norm_topk_probtrue
num_attention_heads64
num_experts_per_tok8
num_hidden_layers45
num_key_value_heads64
num_nextn_predict_layers1
output_router_logitsfalse
pad_token_id154820
q_lora_rank1536
qk_head_dim256
qk_nope_head_dim256
qk_rope_head_dim0
rms_norm_eps0.00001
routed_scaling_factor2.5
router_aux_loss_coef0.001
scoring_funcsigmoid
swiglu_limit10
topk_group1
topk_methodnoaux_tc
use_cachetrue
v_head_dim256
vocab_size154880