diff --git a/src/models/gemma3n.cpp b/src/models/gemma3n.cpp
index f2e5ae6c8..7848f9f59 100644
--- a/src/models/gemma3n.cpp
+++ b/src/models/gemma3n.cpp
@@ -25,14 +25,14 @@ void llama_model_gemma3n::load_arch_tensors(llama_model_loader &) {
     const int64_t laurel_rank  = hparams.laurel_rank;
     const int64_t n_embd_altup = hparams.n_embd_altup;
 
+    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
+
     output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
     // if output is NULL, init from the input tok embed
     if (output == NULL) {
         output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
     }
 
-    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
-
     altup_proj        = create_tensor(tn(LLM_TENSOR_ALTUP_PROJ,        "weight"), {n_embd, n_embd, n_altup - 1}, 0);
     altup_unembd_proj = create_tensor(tn(LLM_TENSOR_ALTUP_UNEMBD_PROJ, "weight"), {n_embd, n_embd, n_altup - 1}, 0);
 
diff --git a/src/models/gemma4.cpp b/src/models/gemma4.cpp
index f4f80d396..42d6a7d47 100644
--- a/src/models/gemma4.cpp
+++ b/src/models/gemma4.cpp
@@ -47,14 +47,14 @@ void llama_model_gemma4::load_arch_tensors(llama_model_loader &) {
         throw std::runtime_error("Gemma 4 requires n_embd_head_k_swa == n_embd_head_v_swa");
     }
 
+    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
+
     output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
     // if output is NULL, init from the input tok embed
     if (output == NULL) {
         output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
     }
 
-    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
-
     if (n_embd_per_layer > 0) {
         per_layer_tok_embd   = create_tensor(tn(LLM_TENSOR_PER_LAYER_TOKEN_EMBD, "weight"),    {n_embd_per_layer * n_layer, n_vocab}, TENSOR_READ_LAZY);
         per_layer_model_proj = create_tensor(tn(LLM_TENSOR_PER_LAYER_MODEL_PROJ, "weight", 0), {n_embd, n_embd_per_layer * n_layer}, 0);