diff --git a/computility-run.yaml b/computility-run.yaml
index 92dd03b0..56695b53 100644
--- a/computility-run.yaml
+++ b/computility-run.yaml
@@ -9,9 +9,9 @@ command:
         cp /workspace/qwen3_6_scripts/serving_chat.py "${VLLM_ROOT}/entrypoints/openai/serving_chat.py" 2>/dev/null && echo '[runtime] serving_chat.py redeployed' || echo '[runtime] serving_chat.py redeploy skipped';
         cp /workspace/qwen3_6_scripts/multimodal_utils.py "${VLLM_ROOT}/multimodal/utils.py" 2>/dev/null && echo '[runtime] multimodal_utils.py redeployed' || echo '[runtime] multimodal_utils.py redeploy skipped';
         cp /workspace/qwen3_6_scripts/envs.py "${VLLM_ROOT}/envs.py" 2>/dev/null && echo '[runtime] envs.py redeployed' || echo '[runtime] envs.py redeploy skipped';
-        find "${VLLM_ROOT}" -name '*.pyc' -path '*/openai/*' -delete 2>/dev/null;
-        find "${VLLM_ROOT}" -name '*.pyc' -path '*/multimodal/*' -delete 2>/dev/null;
-        find "${VLLM_ROOT}" -maxdepth 1 -name 'envs*.pyc' -delete 2>/dev/null;
+        cp /workspace/qwen3_6_scripts/vendor_overrides/vllm/sampling_params.py "${VLLM_ROOT}/sampling_params.py" 2>/dev/null && echo '[runtime] sampling_params.py redeployed' || echo '[runtime] sampling_params.py redeploy skipped';
+        find "${VLLM_ROOT}" -name '*.pyc' -delete 2>/dev/null;
+        find "${VLLM_ROOT}" -name '__pycache__' -type d -exec rm -rf {} + 2>/dev/null;
         exec python3 -m vllm.entrypoints.openai.api_server
         --model /model
         --served-model-name llm
diff --git a/qwen3_6_scripts/serving_chat.py b/qwen3_6_scripts/serving_chat.py
index 8b5ceeab..27d9e0aa 100644
--- a/qwen3_6_scripts/serving_chat.py
+++ b/qwen3_6_scripts/serving_chat.py
@@ -396,8 +396,23 @@ class OpenAIServingChat(OpenAIServing):
             # OpenAI API: max_completion_tokens takes precedence over max_tokens
             if request.max_completion_tokens is not None and request.max_tokens is None:
                 request.max_tokens = request.max_completion_tokens
-            default_max_tokens = min(self.max_model_len - len(
-                prompt_inputs["prompt_token_ids"]), 8192)
+
+            # [BI100] Adaptive max_tokens based on prompt length.
+            _prompt_len = len(prompt_inputs["prompt_token_ids"])
+            if _prompt_len > 65536:
+                _adaptive_cap = 256
+            elif _prompt_len > 32768:
+                _adaptive_cap = 512
+            elif _prompt_len > 16384:
+                _adaptive_cap = 1024
+            else:
+                _adaptive_cap = 8192
+
+            if request.max_tokens is not None:
+                request.max_tokens = min(request.max_tokens, _adaptive_cap)
+
+            default_max_tokens = min(self.max_model_len - _prompt_len,
+                                     _adaptive_cap)
             if request.use_beam_search:
                 sampling_params = request.to_beam_search_params(
                     default_max_tokens)
@@ -412,7 +427,7 @@ class OpenAIServingChat(OpenAIServing):
                              prompt_adapter_request=prompt_adapter_request)
 
             engine_inputs = TokensPrompt(
-                prompt_token_ids=prompt_inputs["prompt_token_ids"]), 8192)
+                prompt_token_ids=prompt_inputs["prompt_token_ids"])
             if mm_data is not None:
                 engine_inputs["multi_modal_data"] = mm_data