diff --git a/paddleformers/transformers/minimax_m2/modeling.py b/paddleformers/transformers/minimax_m2/modeling.py
index 45aac83caf1..2138b80a449 100644
--- a/paddleformers/transformers/minimax_m2/modeling.py
+++ b/paddleformers/transformers/minimax_m2/modeling.py
@@ -171,6 +171,7 @@ def _add_layer_slice_config(prefix):
             # FFN gate_up weights
             if ffn_slice_fn is not None:
                 moe_intermediate_size = config.moe_intermediate_size
+                intermediate_size = config.intermediate_size
 
                 # Fused experts
                 param_name = f"{prefix}.mlp.experts.up_gate_proj.weight"
@@ -181,6 +182,13 @@ def _add_layer_slice_config(prefix):
                     ffn_slice_fn,
                     {"intermediate_size": moe_intermediate_size},
                 )
+                slice_config[f"{prefix}.mlp.grouped_gemm_experts.weight1"] = (
+                    ffn_slice_fn,
+                    {"intermediate_size": moe_intermediate_size},
+                )
+                # Common experts
+                param_name = f"{prefix}.mlp.up_gate_proj.weight"
+                slice_config[param_name] = (ffn_slice_fn, {"intermediate_size": intermediate_size})
 
                 # Routed experts (per-expert)
                 if hasattr(config, "n_routed_experts") and config.n_routed_experts > 0:
@@ -193,6 +201,7 @@ def _add_layer_slice_config(prefix):
             # Fused MoE weights (grouped_gemm)
             if moe_grouped_gemm and fused_moe_fn is not None:
                 slice_config[f"{prefix}.mlp.experts.down_proj.weight"] = (fused_moe_fn, {})
+                slice_config[f"{prefix}.mlp.grouped_gemm_experts.weight2"] = (fused_moe_fn, {})
 
             # MLA weights
             if use_mla and mla_slice_fn is not None:
@@ -244,6 +253,8 @@ def _add_layer_slice_config(prefix):
             num_nextn_predict_layers = config.num_nextn_predict_layers if config.num_nextn_predict_layers else 0
         for layer_idx in range(num_nextn_predict_layers):
             _add_layer_slice_config(f"model.layers.{num_hidden_layers + layer_idx}")
+        for layer_idx in range(num_nextn_predict_layers):
+            _add_layer_slice_config(f"model.layers.{num_hidden_layers + layer_idx}.transformer_layer")
 
         return slice_config