diff --git a/python/sglang/srt/managers/scheduler.py b/python/sglang/srt/managers/scheduler.py
index cfbde332fcf4..3ea790ddd6b1 100644
--- a/python/sglang/srt/managers/scheduler.py
+++ b/python/sglang/srt/managers/scheduler.py
@@ -41,6 +41,7 @@
     create_grammar_backend,
 )
 from sglang.srt.disaggregation.decode import (
+    CLIP_MAX_NEW_TOKEN,
     DecodePreallocQueue,
     DecodeTransferQueue,
     SchedulerDisaggregationDecodeMixin,
@@ -1685,20 +1686,29 @@ def _get_swa_token_info(self):
         )
 
     def get_next_batch_to_run(self) -> Optional[ScheduleBatch]:
+        if self.is_hybrid:
+            rem_total_tokens = min(
+                self.token_to_kv_pool_allocator.full_available_size()
+                + self.tree_cache.full_evictable_size(),
+                self.token_to_kv_pool_allocator.swa_available_size()
+                + self.tree_cache.swa_evictable_size(),
+            )
+        elif self.is_hybrid_gdn:
+            rem_total_tokens = (
+                self.token_to_kv_pool_allocator.available_size()
+                + self.tree_cache.full_evictable_size()
+            )
+        else:
+            rem_total_tokens = (
+                self.token_to_kv_pool_allocator.available_size()
+                + self.tree_cache.evictable_size()
+            )
         # Merge the prefill batch into the running batch
         chunked_req_to_exclude = set()
         if self.chunked_req:
             # Move the chunked request out of the batch so that we can merge
             # only finished requests to running_batch.
             chunked_req_to_exclude.add(self.chunked_req)
-            self.tree_cache.cache_unfinished_req(self.chunked_req, chunked=True)
-            # chunked request keeps its rid but will get a new req_pool_idx
-            if self.tp_worker.model_runner.mambaish_config is not None:
-                self.req_to_token_pool.free(
-                    self.chunked_req.req_pool_idx, free_mamba_cache=False
-                )
-            else:
-                self.req_to_token_pool.free(self.chunked_req.req_pool_idx)
         if self.last_batch and self.last_batch.forward_mode.is_extend():
             if self.last_batch.chunked_req is not None:
                 # In the context pipeline parallelism, after the last chunk, the current microbatch still track outdated chunked_req.
@@ -1722,7 +1732,29 @@ def get_next_batch_to_run(self) -> Optional[ScheduleBatch]:
                     # Merge running_batch with prefill batch
                     self.running_batch.merge_batch(self.last_batch)
 
-        new_batch = self.get_new_batch_prefill()
+        rem_total_tokens -= sum(
+            [
+                min(
+                    r.sampling_params.max_new_tokens - len(r.output_ids),
+                    CLIP_MAX_NEW_TOKEN,
+                )
+                * self.new_token_ratio
+                for r in self.running_batch.reqs
+            ]
+        )
+        if self.chunked_req and rem_total_tokens > 0:
+            self.tree_cache.cache_unfinished_req(self.chunked_req, chunked=True)
+            # chunked request keeps its rid but will get a new req_pool_idx
+            if self.tp_worker.model_runner.mambaish_config is not None:
+                self.req_to_token_pool.free(
+                    self.chunked_req.req_pool_idx, free_mamba_cache=False
+                )
+            else:
+                self.req_to_token_pool.free(self.chunked_req.req_pool_idx)
+        if rem_total_tokens > 0:
+            new_batch = self.get_new_batch_prefill()
+        else:
+            new_batch = None
 
         need_mlp_sync = self.require_mlp_sync
         if need_mlp_sync and not self.spec_algorithm.is_none():