diff --git a/src/llama-build-context.cpp b/src/llama-build-context.cpp
index 41896240..67955280 100644
--- a/src/llama-build-context.cpp
+++ b/src/llama-build-context.cpp
@@ -7557,47 +7557,21 @@ struct ggml_tensor * llm_build_context::build_mtp_tail(
     ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
     cb(ffn_inp, "mtp_ffn_inp", il);
 
-    cur = llm_build_norm(ctx0, ffn_inp, hparams, mtp_layer.attn_post_norm, NULL, LLM_NORM_RMS, cb, il);
-    cb(cur, "attn_post_norm", il);
+    cur = llm_build_std_moe_ffn(ctx0, lctx, mtp_layer.ffn_norm, ffn_inp,
+                    mtp_layer.ffn_gate_inp,  NULL,
+                    mtp_layer.ffn_up_exps,   NULL,
+                    mtp_layer.ffn_gate_exps, NULL,
+                    mtp_layer.ffn_down_exps, NULL,
+                    mtp_layer.ffn_exp_probs_b,
+                    mtp_layer.ffn_up_shexp,    nullptr,
+                    mtp_layer.ffn_gate_shexp,  nullptr,
+                    mtp_layer.ffn_down_shexp,  nullptr,
+                    n_expert, n_expert_used,
+                    LLM_FFN_SILU, hparams.expert_weights_norm, true, hparams.expert_weights_scale,
+                    (llm_expert_gating_func_type) hparams.expert_gating_func,
+                    LLM_FFN_SILU, cb, il, gf, true, mtp_layer.ffn_up_gate_exps);
+    cb(cur, "ffn_out", il);
 
-    // moe ffn for nextn block
-    {
-        // Routed Experts
-        ggml_tensor * routed_out = llm_build_std_moe_ffn(ctx0, lctx, 
-                        NULL, // Norm handled above
-                        cur,  // Input (Normed)
-                        mtp_layer.ffn_gate_inp,  NULL,
-                        mtp_layer.ffn_up_exps,   NULL,
-                        mtp_layer.ffn_gate_exps, NULL,
-                        mtp_layer.ffn_down_exps, NULL,
-                        mtp_layer.ffn_exp_probs_b,
-                        nullptr,    nullptr, // we don't have shared expert biases?
-                        nullptr,  nullptr,
-                        nullptr,  nullptr,
-                        n_expert, n_expert_used,
-                        LLM_FFN_SILU, hparams.expert_weights_norm, true, hparams.expert_weights_scale,
-                        (llm_expert_gating_func_type) hparams.expert_gating_func,
-                        LLM_FFN_SILU, cb, il, gf, true, mtp_layer.ffn_up_gate_exps);
-        cb(routed_out, "ffn_moe_out", il);
-
-        // Shared Expert FFN
-        ggml_tensor * shared_out = llm_build_ffn(ctx0, lctx, 
-                NULL, // Norm handled above
-                cur,  // Input
-                mtp_layer.ffn_up_shexp,   NULL, NULL,
-                mtp_layer.ffn_gate_shexp, NULL, NULL,
-                mtp_layer.ffn_down_shexp, NULL, NULL,
-                NULL,
-                LLM_FFN_SILU, LLM_FFN_PAR, cb, il, gf, true);
-        cb(shared_out, "ffn_shexp_out", il);
-
-        // Sum and Residual
-        cur = ggml_add(ctx0, routed_out, shared_out);
-        cb(cur, "ffn_out", il);
-
-        cur = ggml_add(ctx0, cur, ffn_inp);
-        cb(cur, "mtp_ffn_out_resid", il);
-    }
     cur = llm_build_norm(ctx0, cur, hparams, mtp_layer.nextn.shared_head_norm, NULL, LLM_NORM_RMS, cb, il);
     cb(cur, "result_norm", -1);