diff --git a/python/sglang/srt/layers/radix_attention.py b/python/sglang/srt/layers/radix_attention.py
index b9ea6ad85be..6ee4a31a144 100644
--- a/python/sglang/srt/layers/radix_attention.py
+++ b/python/sglang/srt/layers/radix_attention.py
@@ -4,6 +4,8 @@
 import torch
 from torch import nn
 
+from flashinfer.cascade import merge_state
+
 from sglang.global_config import global_config
 from sglang.srt.layers.extend_attention import extend_attention_fwd
 from sglang.srt.layers.token_attention import token_attention_fwd
@@ -95,8 +97,6 @@ def decode_forward_triton(self, q, k, v, input_metadata: InputMetadata):
         return o
 
     def prefill_forward_flashinfer(self, q, k, v, input_metadata: InputMetadata):
-        self.store_kv_cache(k, v, input_metadata)
-
         o1, s1 = input_metadata.flashinfer_prefill_wrapper_ragged.forward_return_lse(
             q.contiguous().view(-1, self.tp_q_head_num, self.head_dim),
             k.contiguous().view(-1, self.tp_k_head_num, self.head_dim),
@@ -117,10 +117,10 @@ def prefill_forward_flashinfer(self, q, k, v, input_metadata: InputMetadata):
                 logits_soft_cap=self.logit_cap,
             )
 
-            from flashinfer.cascade import merge_state
-
             o, _ = merge_state(o1, s1, o2, s2)
 
+        self.store_kv_cache(k, v, input_metadata)
+
         if input_metadata.total_num_tokens >= global_config.layer_sync_threshold:
             torch.cuda.synchronize()
 
diff --git a/python/sglang/srt/managers/controller/model_runner.py b/python/sglang/srt/managers/controller/model_runner.py
index 0bb869cf793..4eeaeac76ec 100644
--- a/python/sglang/srt/managers/controller/model_runner.py
+++ b/python/sglang/srt/managers/controller/model_runner.py
@@ -408,7 +408,7 @@ def init_flash_infer(self):
                 use_tensor_cores = False
 
             workspace_buffers = torch.empty(
-                3, 96 * 1024 * 1024, dtype=torch.uint8, device="cuda"
+                2, 96 * 1024 * 1024, dtype=torch.uint8, device="cuda"
             )
             self.flashinfer_prefill_wrapper_ragged = (
                 BatchPrefillWithRaggedKVCacheWrapper(workspace_buffers[0], "NHD")
@@ -417,7 +417,7 @@ def init_flash_infer(self):
                 workspace_buffers[1], "NHD"
             )
             self.flashinfer_decode_wrapper = BatchDecodeWithPagedKVCacheWrapper(
-                workspace_buffers[2], "NHD", use_tensor_cores=use_tensor_cores
+                workspace_buffers[0], "NHD", use_tensor_cores=use_tensor_cores
             )
         else:
             self.flashinfer_prefill_wrapper_ragged = (