diff --git a/lightllm/common/kv_cache_mem_manager/qwen3next_mem_manager.py b/lightllm/common/kv_cache_mem_manager/qwen3next_mem_manager.py
index f65a849df..c8f69dac8 100644
--- a/lightllm/common/kv_cache_mem_manager/qwen3next_mem_manager.py
+++ b/lightllm/common/kv_cache_mem_manager/qwen3next_mem_manager.py
@@ -71,7 +71,17 @@ def _free_linear_att_buffers(self):
     def write_to_shm(self, req_manager):
         self.req_to_conv_state = req_manager.req_to_conv_state
         self.req_to_ssm_state = req_manager.req_to_ssm_state
-        return super().write_to_shm(req_manager)
+        # super().write_to_shm() 会用 ForkingPickler 序列化本对象，torch 在 dump 时会把
+        # CPU tensor 的 storage 原地迁到共享内存，使本进程大页 state cache 原本
+        # pinned(cudaHostAlloc) 的内存退化为普通 shm mmap，之后 Triton kernel 携带该指针
+        # 启动会报 "Pointer argument cannot be accessed from Triton (cpu tensor?)"。
+        # 跨进程消费方并不使用 cpu 侧大页 state cache，序列化期间临时剔除以保住 pinned。
+        big_page_buffers = self.linear_att_big_page_buffers
+        self.linear_att_big_page_buffers = None
+        try:
+            return super().write_to_shm(req_manager)
+        finally:
+            self.linear_att_big_page_buffers = big_page_buffers
 
     def alloc_paged_kv_move_buffer(self, page_num, page_size) -> torch.Tensor:
         kv_move_buffer = super().alloc_paged_kv_move_buffer(page_num, page_size)