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model: add Qwen3-Omni Thinker support (qwen3omnimoe) #18420

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851cb0d
model: add Qwen3-Omni Thinker support (qwen3omnimoe)
TrevorS Dec 31, 2025
d4ee36e
convert: simplify Qwen3OmniMoeModel per review feedback
TrevorS Dec 31, 2025
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18 changes: 18 additions & 0 deletions convert_hf_to_gguf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4317,6 +4317,24 @@ def set_vocab(self):
super().set_vocab()


@ModelBase.register("Qwen3OmniMoeForConditionalGeneration")
class Qwen3OmniMoeModel(Qwen2MoeModel):
model_arch = gguf.MODEL_ARCH.QWEN3OMNIMOE

def set_vocab(self):
super().set_vocab()
# Qwen3-Omni lacks tokenizer.json, so token IDs must be set explicitly
self.gguf_writer.add_eos_token_id(151645) # <|im_end|> - required for generation
self.gguf_writer.add_pad_token_id(151643) # <|endoftext|> - required for batching
Comment on lines +4326 to +4328
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@CISC CISC Jan 1, 2026

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The comment is incorrect, it's because they for some reason are explicitly set to null in config.json.


def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
if name.startswith("thinker."):
name = name.replace("thinker.", "", 1)
if name.startswith(("audio_tower.", "visual.", "talker.", "code2wav.")):
return []
return super().modify_tensors(data_torch, name, bid)


@ModelBase.register("Qwen3NextForCausalLM")
class Qwen3NextModel(Qwen2MoeModel):
model_arch = gguf.MODEL_ARCH.QWEN3NEXT
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22 changes: 22 additions & 0 deletions gguf-py/gguf/constants.py
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Original file line number Diff line number Diff line change
Expand Up @@ -372,6 +372,7 @@ class MODEL_ARCH(IntEnum):
QWEN3NEXT = auto()
QWEN3VL = auto()
QWEN3VLMOE = auto()
QWEN3OMNIMOE = auto()
PHI2 = auto()
PHI3 = auto()
PHIMOE = auto()
Expand Down Expand Up @@ -769,6 +770,7 @@ class MODEL_TENSOR(IntEnum):
MODEL_ARCH.QWEN3NEXT: "qwen3next",
MODEL_ARCH.QWEN3VL: "qwen3vl",
MODEL_ARCH.QWEN3VLMOE: "qwen3vlmoe",
MODEL_ARCH.QWEN3OMNIMOE: "qwen3omnimoe",
MODEL_ARCH.PHI2: "phi2",
MODEL_ARCH.PHI3: "phi3",
MODEL_ARCH.PHIMOE: "phimoe",
Expand Down Expand Up @@ -1720,6 +1722,26 @@ class MODEL_TENSOR(IntEnum):
MODEL_TENSOR.FFN_DOWN_EXP,
MODEL_TENSOR.FFN_UP_EXP,
],
MODEL_ARCH.QWEN3OMNIMOE: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.OUTPUT,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_Q_NORM,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_K_NORM,
MODEL_TENSOR.ATTN_V,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_GATE_INP,
MODEL_TENSOR.FFN_GATE_EXP,
MODEL_TENSOR.FFN_DOWN_EXP,
MODEL_TENSOR.FFN_UP_EXP,
MODEL_TENSOR.FFN_GATE_SHEXP,
MODEL_TENSOR.FFN_DOWN_SHEXP,
MODEL_TENSOR.FFN_UP_SHEXP,
],
MODEL_ARCH.PLAMO: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
Expand Down
22 changes: 22 additions & 0 deletions src/llama-arch.cpp
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Expand Up @@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_QWEN3NEXT, "qwen3next" },
{ LLM_ARCH_QWEN3VL, "qwen3vl" },
{ LLM_ARCH_QWEN3VLMOE, "qwen3vlmoe" },
{ LLM_ARCH_QWEN3OMNIMOE, "qwen3omnimoe" },
{ LLM_ARCH_PHI2, "phi2" },
{ LLM_ARCH_PHI3, "phi3" },
{ LLM_ARCH_PHIMOE, "phimoe" },
Expand Down Expand Up @@ -935,6 +936,27 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
LLM_TENSOR_FFN_DOWN_EXPS,
LLM_TENSOR_FFN_UP_EXPS,
};
case LLM_ARCH_QWEN3OMNIMOE:
return {
LLM_TENSOR_TOKEN_EMBD,
LLM_TENSOR_OUTPUT_NORM,
LLM_TENSOR_OUTPUT,
LLM_TENSOR_ATTN_NORM,
LLM_TENSOR_ATTN_Q,
LLM_TENSOR_ATTN_Q_NORM,
LLM_TENSOR_ATTN_K,
LLM_TENSOR_ATTN_K_NORM,
LLM_TENSOR_ATTN_V,
LLM_TENSOR_ATTN_OUT,
LLM_TENSOR_FFN_NORM,
LLM_TENSOR_FFN_GATE_INP,
LLM_TENSOR_FFN_GATE_EXPS,
LLM_TENSOR_FFN_DOWN_EXPS,
LLM_TENSOR_FFN_UP_EXPS,
LLM_TENSOR_FFN_GATE_SHEXP,
LLM_TENSOR_FFN_DOWN_SHEXP,
LLM_TENSOR_FFN_UP_SHEXP,
};
case LLM_ARCH_QWEN3NEXT:
return {
LLM_TENSOR_TOKEN_EMBD,
Expand Down
1 change: 1 addition & 0 deletions src/llama-arch.h
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,7 @@ enum llm_arch {
LLM_ARCH_QWEN3NEXT,
LLM_ARCH_QWEN3VL,
LLM_ARCH_QWEN3VLMOE,
LLM_ARCH_QWEN3OMNIMOE,
LLM_ARCH_PHI2,
LLM_ARCH_PHI3,
LLM_ARCH_PHIMOE,
Expand Down
67 changes: 67 additions & 0 deletions src/llama-model.cpp
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Expand Up @@ -1144,6 +1144,18 @@ void llama_model::load_hparams(llama_model_loader & ml) {
default: type = LLM_TYPE_UNKNOWN;
}
} break;
case LLM_ARCH_QWEN3OMNIMOE:
{
// Qwen3-Omni Thinker: Qwen3MOE with M-RoPE and shared experts
ml.get_key_or_arr(LLM_KV_ROPE_DIMENSION_SECTIONS, hparams.rope_sections, 4, true);
ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_ff_exp, false);
ml.get_key(LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH, hparams.n_ff_shexp, false);
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
switch (hparams.n_layer) {
case 48: type = LLM_TYPE_30B; break;
default: type = LLM_TYPE_UNKNOWN;
}
} break;
case LLM_ARCH_PHI2:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
Expand Down Expand Up @@ -3642,6 +3654,55 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
layer.ffn_up_exps = create_tensor(tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert}, 0);
}
} break;
case LLM_ARCH_QWEN3OMNIMOE:
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Since this is only Qwen3VLMoe with shared experts added and you are adding shared experts support to qwen3vl-moe.cpp I suggest you do the same here instead of duplicating code.

{
// Qwen3-Omni Thinker: Qwen3MOE with M-RoPE and shared experts
tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);

output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);
output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
if (output == NULL) {
output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
}

for (int i = 0; i < n_layer; ++i) {
auto & layer = layers[i];

layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);

layer.wq = create_tensor(tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_head_k * n_head}, 0);
layer.wk = create_tensor(tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa}, 0);
layer.wv = create_tensor(tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa}, 0);
layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * n_head, n_embd}, 0);

layer.attn_k_norm = create_tensor(tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k}, 0);
layer.attn_q_norm = create_tensor(tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k}, 0);

layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);

layer.ffn_gate_inp = create_tensor(tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert}, 0);

if (n_expert == 0) {
throw std::runtime_error("n_expert must be > 0 for QWEN3OMNIMOE");
}
if (n_expert_used == 0) {
throw std::runtime_error("n_expert_used must be > 0 for QWEN3OMNIMOE");
}

// MoE experts
const int64_t n_ff_exp = hparams.n_ff_exp ? hparams.n_ff_exp : n_ff / n_expert_used;
layer.ffn_gate_exps = create_tensor(tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert}, 0);
layer.ffn_down_exps = create_tensor(tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert}, 0);
layer.ffn_up_exps = create_tensor(tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert}, 0);

// Shared expert (optional)
if (hparams.n_ff_shexp > 0) {
layer.ffn_gate_shexp = create_tensor(tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, hparams.n_ff_shexp}, 0);
layer.ffn_down_shexp = create_tensor(tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {hparams.n_ff_shexp, n_embd}, 0);
layer.ffn_up_shexp = create_tensor(tn(LLM_TENSOR_FFN_UP_SHEXP, "weight", i), {n_embd, hparams.n_ff_shexp}, 0);
}
}
} break;
case LLM_ARCH_PHI2:
{
tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
Expand Down Expand Up @@ -7510,6 +7571,11 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const {
{
llm = std::make_unique<llm_build_qwen3vlmoe>(*this, params);
} break;
case LLM_ARCH_QWEN3OMNIMOE:
{
// Reuse Qwen3VLMOE builder - supports M-RoPE and shared experts
llm = std::make_unique<llm_build_qwen3vlmoe>(*this, params);
} break;
case LLM_ARCH_PHI2:
{
llm = std::make_unique<llm_build_phi2>(*this, params);
Expand Down Expand Up @@ -8081,6 +8147,7 @@ llama_rope_type llama_model_rope_type(const llama_model * model) {
return LLAMA_ROPE_TYPE_MROPE;
case LLM_ARCH_QWEN3VL:
case LLM_ARCH_QWEN3VLMOE:
case LLM_ARCH_QWEN3OMNIMOE:
return LLAMA_ROPE_TYPE_IMROPE;

case LLM_ARCH_GLM4:
Expand Down
16 changes: 15 additions & 1 deletion src/models/qwen3vl-moe.cpp
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Expand Up @@ -113,7 +113,21 @@ llm_build_qwen3vlmoe::llm_build_qwen3vlmoe(const llama_model & model, const llm_
LLAMA_EXPERT_GATING_FUNC_TYPE_SOFTMAX,
il);
cb(moe_out, "ffn_moe_out", il);
cur = moe_out;

// Shared expert (optional, for QWEN3OMNIMOE)
if (model.layers[il].ffn_up_shexp != nullptr) {
ggml_tensor * ffn_shexp =
build_ffn(cur,
model.layers[il].ffn_up_shexp, nullptr, nullptr,
model.layers[il].ffn_gate_shexp, nullptr, nullptr,
model.layers[il].ffn_down_shexp, nullptr, nullptr,
nullptr, LLM_FFN_SILU, LLM_FFN_PAR, il);
cb(ffn_shexp, "ffn_shexp", il);
cur = ggml_add(ctx0, moe_out, ffn_shexp);
cb(cur, "ffn_out", il);
} else {
cur = moe_out;
}

cur = ggml_add(ctx0, cur, ffn_inp);

Expand Down
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