diff --git a/vllm/model_executor/models/qwen3_dflash.py b/vllm/model_executor/models/qwen3_dflash.py
index dcc23bc409..231ed646e0 100644
--- a/vllm/model_executor/models/qwen3_dflash.py
+++ b/vllm/model_executor/models/qwen3_dflash.py
@@ -247,8 +247,10 @@ class DFlashQwen3Model(nn.Module):
             [
                 DFlashQwen3DecoderLayer(
                     current_vllm_config,
-                    prefix=maybe_prefix(prefix, f"layers.{layer_idx + start_layer_id}"),
                     config=self.config,
+                    cache_config=current_vllm_config.cache_config,
+                    quant_config=self.quant_config,
+                    prefix=maybe_prefix(prefix, f"layers.{layer_idx + start_layer_id}"),
                 )
                 for layer_idx in range(self.config.num_hidden_layers)
             ]
diff --git a/vllm/v1/spec_decode/llm_base_proposer.py b/vllm/v1/spec_decode/llm_base_proposer.py
index 8c9f2f7bae..dc50867329 100644
--- a/vllm/v1/spec_decode/llm_base_proposer.py
+++ b/vllm/v1/spec_decode/llm_base_proposer.py
@@ -116,7 +116,7 @@ class SpecDecodeBaseProposer:
 
         self.max_batch_size = vllm_config.scheduler_config.max_num_seqs
         self.max_num_tokens = vllm_config.scheduler_config.max_num_batched_tokens
-        self.token_arange_np = np.arange(self.max_num_tokens)
+        self.token_arange_np = np.arange(self.max_num_tokens, dtype=np.int32)
 
         # Can be specialized by methods like DFlash to reduce the limit
         self.max_query_tokens = self.max_num_tokens