diff --git a/cpp/tensorrt_llm/batch_manager/createNewDecoderRequests.cpp b/cpp/tensorrt_llm/batch_manager/createNewDecoderRequests.cpp
index 1d06ac0e860..baa51f47e73 100644
--- a/cpp/tensorrt_llm/batch_manager/createNewDecoderRequests.cpp
+++ b/cpp/tensorrt_llm/batch_manager/createNewDecoderRequests.cpp
@@ -63,7 +63,10 @@ void copySequenceLengths(RequestVector const& contextRequests, DecoderInputBuffe
     SizeType32 batchIdx{0};
     for (auto const& llmReq : contextRequests)
     {
-        auto const currentSequenceLen = llmReq->mPromptLen + llmReq->getMaxNumGeneratedTokens();
+        auto const disaggFirstGenTokenSize
+            = llmReq->getContextPhaseParams() ? llmReq->getContextPhaseParams().value().getFirstGenTokens().size() : 0;
+        auto const currentSequenceLen
+            = llmReq->mPromptLen + llmReq->getMaxNumGeneratedTokens() + disaggFirstGenTokenSize;
         // Get position of the current sequence in the decoder
         auto const seqSlot = llmReq->mSeqSlot.value();
         batchSlotsRange[batchIdx] = seqSlot;
diff --git a/tensorrt_llm/_torch/pyexecutor/_util.py b/tensorrt_llm/_torch/pyexecutor/_util.py
index 29f1c5d3ac8..0bfba50a9c9 100644
--- a/tensorrt_llm/_torch/pyexecutor/_util.py
+++ b/tensorrt_llm/_torch/pyexecutor/_util.py
@@ -520,7 +520,6 @@ def create_py_executor_instance(
     cache_transceiver_config = executor_config.cache_transceiver_config
     kv_cache_transceiver = create_kv_cache_transceiver(
         mapping, kv_cache_manager, attention_type, cache_transceiver_config)
-
     return PyExecutor(
         resource_manager,
         scheduler,
diff --git a/tensorrt_llm/_torch/pyexecutor/sampler.py b/tensorrt_llm/_torch/pyexecutor/sampler.py
index b4dfdf25d45..31e17c1247d 100644
--- a/tensorrt_llm/_torch/pyexecutor/sampler.py
+++ b/tensorrt_llm/_torch/pyexecutor/sampler.py
@@ -751,8 +751,7 @@ def update_requests_single_beam_single_step(self, state: SampleStateTRTLLM):
 
         reqs_with_new_tokens = [
             r for r in reqs
-            if (sequence_lengths_host_data[r.py_seq_slot] > r.get_num_tokens(0)
-                or self.is_trt_overlap)
+            if (sequence_lengths_host_data[r.py_seq_slot] > r.get_num_tokens(0))
         ]
 
         # Add new tokens
@@ -821,7 +820,6 @@ def update_requests_multiple_beams_or_drafting(self,
             for beam in range(beam_width):
                 seq_len = sequence_lengths_host_data[seq_slot * beam_width +
                                                      beam]
-                seq_len = seq_len + 1 if self.is_trt_overlap else seq_len
                 num_new_tokens[beam] = min(
                     num_generated_tokens,
                     seq_len - request.get_num_tokens(beam))