diff --git a/src/graphs/build_mistral3.cpp b/src/graphs/build_mistral3.cpp
index 1d37c5c4..4be53b23 100644
--- a/src/graphs/build_mistral3.cpp
+++ b/src/graphs/build_mistral3.cpp
@@ -25,42 +25,31 @@ ggml_cgraph * llm_build_context::build_mistral3() {
 
     ggml_tensor * KQ_mask = build_inp_KQ_mask();
 
-    ggml_tensor * inp_out_ids = build_inp_out_ids();
+    ggml_tensor * inp_out_ids = n_tokens > 1 ? build_inp_out_ids() : nullptr;
 
     //const float kq_scale = hparams.f_attention_scale == 0.0f ? 1.0f/sqrtf(float(n_embd_head)) : hparams.f_attention_scale;
     const float kq_scale = hparams.f_attention_scale == 0.0f ? 1.0f/sqrtf(float(n_embd_head)) : 1.f;
 
     for (int il = 0; il < n_layer; ++il) {
-        ggml_tensor * inpSA = inpL;
 
         auto rope_factors = build_rope_factors(il);
 
-        cur = build_std_attention(gf, model.layers[il].attn_norm, inpL, inp_pos, nullptr, rope_factors, KQ_mask,
-                nullptr, inp_attn_scale, kq_scale, hparams.f_attention_scale, 0, il);
-
-        if (il == n_layer - 1 && inp_out_ids) {
-            cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
-            inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
-            cb(cur, "last_attn", il);
-            cb(inpSA, "last_ffn_inp", il);
-        }
-
-        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
-        cb(ffn_inp, "ffn_inp", il);
+        cur = build_std_attention(gf, model.layers[il].attn_norm, inpL, inp_pos, il == n_layer - 1 ? inp_out_ids : nullptr,
+                rope_factors, KQ_mask, nullptr, inp_attn_scale, kq_scale, hparams.f_attention_scale, 0, il, true, false, true);
 
         // feed-forward network (non-MoE)
         if (model.layers[il].ffn_gate_inp == nullptr) {
             // non-MoE
-            cur = llm_build_ffn(ctx0, lctx, model.layers[il].ffn_norm, ffn_inp,
+            cur = llm_build_ffn(ctx0, lctx, model.layers[il].ffn_norm, cur,
                     model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   nullptr,
                     model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, nullptr,
                     model.layers[il].ffn_down, model.layers[il].ffn_down_b, nullptr,
                     NULL,
-                    LLM_FFN_SILU, LLM_FFN_PAR, cb, il, gf);
+                    LLM_FFN_SILU, LLM_FFN_PAR, cb, il, gf, true);
             cb(cur, "ffn_out", il);
         } else {
             // MoE branch
-            cur = llm_build_std_moe_ffn(ctx0, lctx, model.layers[il].ffn_norm, ffn_inp,
+            cur = llm_build_std_moe_ffn(ctx0, lctx, model.layers[il].ffn_norm, cur,
                     model.layers[il].ffn_gate_inp,  nullptr,
                     model.layers[il].ffn_up_exps,   nullptr,
                     model.layers[il].ffn_gate_exps, nullptr,
@@ -72,9 +61,8 @@ ggml_cgraph * llm_build_context::build_mistral3() {
                     n_expert, n_expert_used,
                     LLM_FFN_SILU, true, false, 0.0f,
                     LLM_EXPERT_GATING_FUNC_SOFTMAX,
-                    LLM_FFN_SILU, cb, il, gf);
+                    LLM_FFN_SILU, cb, il, gf, true);
         }
-        cur = ggml_add(ctx0, cur, ffn_inp);
         cb(cur, "ffn_out", il);
 
         cur = lctx.cvec.apply_to(ctx0, cur, il);