diff --git a/src/models/gemma3n-iswa.cpp b/src/models/gemma3n-iswa.cpp
index 4b6817c96a..ad982808bc 100644
--- a/src/models/gemma3n-iswa.cpp
+++ b/src/models/gemma3n-iswa.cpp
@@ -250,27 +250,29 @@ ggml_tensor * llm_build_gemma3n_iswa::calc_magnitude(ggml_tensor * x) {
 ggml_tensor * llm_build_gemma3n_iswa::build_inp_per_layer() {
     auto inp = std::make_unique<llm_graph_input_embd>(n_embd);
     ggml_tensor * inp_per_layer;
+    float tok_embd_scale = sqrtf((float) n_embd_altup);
     if (ubatch.token) {
         inp->tokens = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, ubatch.n_tokens);
         ggml_set_input(inp->tokens);
         res->t_inp_tokens = inp->tokens;
-        inp_per_layer = ggml_get_rows(ctx0, model.per_layer_tok_embd, inp->tokens);
+        inp_per_layer = ggml_get_rows  (ctx0, model.per_layer_tok_embd, inp->tokens);
         inp_per_layer = ggml_reshape_3d(ctx0, inp_per_layer, n_embd_altup, n_layer, n_tokens);
-        inp_per_layer = ggml_scale(ctx0, inp_per_layer, sqrtf((float) n_embd_altup));
+        inp_per_layer = ggml_scale     (ctx0, inp_per_layer, tok_embd_scale);
         cb(inp_per_layer, "inp_per_layer_selected", -1);
         res->add_input(std::move(inp));
     } else {
-        // Vision embedding path: use padding token (ID=0) embedding
+        // Multimodal embedding path: use padding token (ID=0) embedding
         // TODO: verify if this is the correct behavior in transformers implementation
         const int64_t embd_size = model.per_layer_tok_embd->ne[0];  // n_embd_altup * n_layer
 
         // Extract and dequantize padding token embedding (row 0)
         ggml_tensor * padding = ggml_view_1d(ctx0, model.per_layer_tok_embd, embd_size, 0);
-        inp_per_layer = ggml_cast(ctx0, padding, GGML_TYPE_F32);
+        inp_per_layer = ggml_cast (ctx0, padding, GGML_TYPE_F32);
+        inp_per_layer = ggml_scale(ctx0, inp_per_layer, tok_embd_scale);
 
         // Reshape to [n_embd_altup, n_layer, 1]
         inp_per_layer = ggml_reshape_3d(ctx0, inp_per_layer, n_embd_altup, n_layer, 1);
-        cb(inp_per_layer, "inp_per_layer_vision", -1);
+        cb(inp_per_layer, "inp_per_layer_multimodal", -1);
     }
     return inp_per_layer;
 }
diff --git a/src/models/gemma4-iswa.cpp b/src/models/gemma4-iswa.cpp
index b3c6c5be2a..405cdadc13 100644
--- a/src/models/gemma4-iswa.cpp
+++ b/src/models/gemma4-iswa.cpp
@@ -265,6 +265,7 @@ ggml_tensor * llm_build_gemma4_iswa::build_inp_per_layer() {
     auto inp = std::make_unique<llm_graph_input_embd>(n_embd);
 
     ggml_tensor * inp_per_layer;
+    float tok_embd_scale = sqrtf((float) n_embd_per_layer);
     if (ubatch.token) {
         inp->tokens = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, ubatch.n_tokens);
         ggml_set_input(inp->tokens);
@@ -272,22 +273,23 @@ ggml_tensor * llm_build_gemma4_iswa::build_inp_per_layer() {
 
         inp_per_layer = ggml_get_rows  (ctx0, model.per_layer_tok_embd, inp->tokens);
         inp_per_layer = ggml_reshape_3d(ctx0, inp_per_layer, n_embd_per_layer, n_layer, n_tokens);
-        inp_per_layer = ggml_scale     (ctx0, inp_per_layer, sqrtf((float) n_embd_per_layer));
+        inp_per_layer = ggml_scale     (ctx0, inp_per_layer, tok_embd_scale);
         cb(inp_per_layer, "inp_per_layer_selected", -1);
 
         res->add_input(std::move(inp));
     } else {
-        // Vision embedding path: use padding token (ID=0) embedding
+        // Multimodal embedding path: use padding token (ID=0) embedding
         // TODO: verify if this is the correct behavior in transformers implementation
         const int64_t embd_size = model.per_layer_tok_embd->ne[0];  // n_embd_per_layer * n_layer
 
         // Extract and dequantize padding token embedding (row 0)
         ggml_tensor * padding = ggml_view_1d(ctx0, model.per_layer_tok_embd, embd_size, 0);
-        inp_per_layer = ggml_cast(ctx0, padding, GGML_TYPE_F32);
+        inp_per_layer = ggml_cast (ctx0, padding, GGML_TYPE_F32);
+        inp_per_layer = ggml_scale(ctx0, inp_per_layer, tok_embd_scale);
 
         // Reshape to [n_embd_per_layer, n_layer, 1]
         inp_per_layer = ggml_reshape_3d(ctx0, inp_per_layer, n_embd_per_layer, n_layer, 1);
-        cb(inp_per_layer, "inp_per_layer_vision", -1);
+        cb(inp_per_layer, "inp_per_layer_multimodal", -1);
     }
     return inp_per_layer;
 }