diff --git a/tensorrt_llm/llmapi/llm.py b/tensorrt_llm/llmapi/llm.py
index ac869d765a5..71d34af1a64 100644
--- a/tensorrt_llm/llmapi/llm.py
+++ b/tensorrt_llm/llmapi/llm.py
@@ -31,7 +31,7 @@
                         GenerationResult, IterationResult, LoRARequest,
                         PostprocWorkerConfig, PromptAdapterRequest)
 from ..executor.postproc_worker import PostprocParams
-from ..executor.utils import (create_mpi_comm_session,
+from ..executor.utils import (RequestError, create_mpi_comm_session,
                               get_spawn_proxy_process_env)
 from ..inputs import (PromptInputs, create_input_processor,
                       create_input_processor_with_hash, get_cache_salt_id,
@@ -686,7 +686,7 @@ def _check_arguments(self, prompt_len: int, query_len: int,
             if self.args.backend == "pytorch" and not self.args.enable_chunked_prefill and not is_gen_only:
                 max_num_tokens = self.args.max_num_tokens
                 if max_num_tokens and prompt_len / self.args.parallel_config.cp_size + query_len > max_num_tokens:
-                    raise ValueError(
+                    raise RequestError(
                         f"The sum of prompt length ({prompt_len/self.args.parallel_config.cp_size}), query length ({query_len}) should not exceed "
                         f"max_num_tokens ({max_num_tokens})")
             return
diff --git a/tests/unittest/llmapi/test_llm.py b/tests/unittest/llmapi/test_llm.py
index f8ffe8fc7bd..87624b61b8e 100644
--- a/tests/unittest/llmapi/test_llm.py
+++ b/tests/unittest/llmapi/test_llm.py
@@ -2393,7 +2393,8 @@ def fail_path():
                   enable_chunked_prefill=False,
                   fast_build=True)
 
-        with pytest.raises(ValueError):
+        # max_num_tokens validation now raises RequestError consistently
+        with pytest.raises(RequestError):
             output = llm.generate_async(
                 "A " * build_config.max_num_tokens,
                 sampling_params=sampling_params,
@@ -2436,13 +2437,9 @@ def _test_llm_capture_request_error(pytorch_backend: bool, tp_size: int = 1):
     )
 
     prompt = 'A ' * 65  # the minimum max_num_tokens is 64
-    if pytorch_backend:
-        # pytorch backend will raise ValueError for max_num_tokens
-        with pytest.raises(ValueError):
-            llm.generate(prompt)
-    else:
-        with pytest.raises(RequestError):
-            llm.generate(prompt)
+    # Both backends now consistently raise RequestError for max_num_tokens validation
+    with pytest.raises(RequestError):
+        llm.generate(prompt)
 
 
 def test_llm_capture_request_error():
diff --git a/tests/unittest/llmapi/test_llm_pytorch.py b/tests/unittest/llmapi/test_llm_pytorch.py
index b9702133152..86f48d31266 100644
--- a/tests/unittest/llmapi/test_llm_pytorch.py
+++ b/tests/unittest/llmapi/test_llm_pytorch.py
@@ -8,7 +8,7 @@
 
 from tensorrt_llm import LLM
 from tensorrt_llm.disaggregated_params import DisaggregatedParams
-from tensorrt_llm.executor import GenerationExecutorWorker
+from tensorrt_llm.executor import GenerationExecutorWorker, RequestError
 from tensorrt_llm.executor.rpc_proxy import GenerationExecutorRpcProxy
 from tensorrt_llm.llmapi import CacheTransceiverConfig, KvCacheConfig
 from tensorrt_llm.llmapi.llm_args import NGramDecodingConfig, PeftCacheConfig
@@ -830,10 +830,13 @@ def test_max_num_token_check(self):
                   kv_cache_config=global_kvcache_config,
                   max_num_tokens=100)
 
-        with pytest.raises(ValueError,
-                           match="should not exceed max_num_tokens"):
-            ids = [random.randint(10, 100) for _ in range(101)]
-            llm.generate([ids])
+        try:
+            with pytest.raises(RequestError,
+                               match="should not exceed max_num_tokens"):
+                ids = [random.randint(10, 100) for _ in range(101)]
+                llm.generate([ids])
+        finally:
+            llm.shutdown()
 
 
 class FailingExecutorWorker(GenerationExecutorWorker):
@@ -962,10 +965,13 @@ def test_max_num_token_check(self):
                   kv_cache_config=global_kvcache_config,
                   max_num_tokens=100)
 
-        with pytest.raises(ValueError,
-                           match="should not exceed max_num_tokens"):
-            ids = [random.randint(10, 100) for _ in range(101)]
-            llm.generate([ids])
+        try:
+            with pytest.raises(RequestError,
+                               match="should not exceed max_num_tokens"):
+                ids = [random.randint(10, 100) for _ in range(101)]
+                llm.generate([ids])
+        finally:
+            llm.shutdown()
 
 
 @skip_ray