diff --git a/cpp/tensorrt_llm/thop/mtpOp.cpp b/cpp/tensorrt_llm/thop/mtpOp.cpp
index 4081834a2acb..dd880f2b7921 100644
--- a/cpp/tensorrt_llm/thop/mtpOp.cpp
+++ b/cpp/tensorrt_llm/thop/mtpOp.cpp
@@ -93,8 +93,8 @@ std::tuple<th::Tensor, th::Tensor> mtp_prepare_drafter_inputs_op(th::Tensor& inp
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////////////
 std::tuple<th::Tensor, th::Tensor> mtp_sampling_and_accepted_draft_tokens_op(th::Tensor& logits,
-    th::Tensor& draftTokens, th::Tensor& targetTokens, th::Tensor& acceptedTokens, th::Tensor& numAcceptedTokens,
-    int64_t numMTPModules, int64_t batchSize, int64_t numContextRequest, int64_t vocabSize)
+    th::Tensor& draftTokens, th::Tensor& targetTokens, int64_t numMTPModules, int64_t batchSize,
+    int64_t numContextRequest, int64_t vocabSize)
 {
     int const numGenerationRequest = batchSize - numContextRequest;
     auto dataType = logits.scalar_type();
@@ -109,6 +109,9 @@ std::tuple<th::Tensor, th::Tensor> mtp_sampling_and_accepted_draft_tokens_op(th:
     TLLM_CHECK(draftTokensSizes[0] == (numGenerationRequest * numMTPModules));
 
     auto stream = at::cuda::getCurrentCUDAStream(logits.get_device());
+    auto acceptedTokens = torch::empty(
+        {batchSize, numMTPModules + 1}, at::TensorOptions().dtype(torch::kInt32).device(logits.device()));
+    auto numAcceptedTokens = torch::ones({batchSize}, at::TensorOptions().dtype(torch::kInt32).device(logits.device()));
 
     // Fill params
     tk::MTPSampleAndAcceptDraftTokensParam params;
@@ -288,7 +291,7 @@ TORCH_LIBRARY_FRAGMENT(trtllm, m)
 {
     m.def(
         "mtp_sampling_and_accepted_draft_tokens_op(Tensor logits, Tensor draftTokens, Tensor "
-        "targetTokens, Tensor acceptedTokens, Tensor numAcceptedTokens, int numMTPModules, "
+        "targetTokens, int numMTPModules, "
         "int batchSize, int numContextRequest, int vocabSize) -> (Tensor, Tensor)");
 }
 
diff --git a/tensorrt_llm/_torch/attention_backend/flashinfer.py b/tensorrt_llm/_torch/attention_backend/flashinfer.py
index f88a2aeb9c45..e7f1b2a31093 100644
--- a/tensorrt_llm/_torch/attention_backend/flashinfer.py
+++ b/tensorrt_llm/_torch/attention_backend/flashinfer.py
@@ -6,6 +6,7 @@
 import flashinfer
 import torch
 from flashinfer.jit.core import check_cuda_arch
+from typing_extensions import Self
 
 from tensorrt_llm.functional import AttentionMaskType
 from tensorrt_llm.models.modeling_utils import QuantConfig
@@ -163,6 +164,19 @@ def __post_init__(self) -> None:
                                                  device='cuda',
                                                  dtype=torch.int)
 
+    def create_cuda_graph_metadata(self,
+                                   max_batch_size: int,
+                                   sub_cross_metadata: bool = False,
+                                   max_draft_tokens: int = 0) -> Self:
+        metadata = super().create_cuda_graph_metadata(max_batch_size,
+                                                      sub_cross_metadata,
+                                                      max_draft_tokens)
+        metadata.max_num_requests = max_batch_size
+        metadata.max_num_tokens = max_batch_size * (1 + max_draft_tokens)
+        # Post init again to make sure all tensors are allocated
+        metadata.__post_init__()
+        return metadata
+
     @property
     def page_size(self) -> int:
         """
@@ -172,9 +186,7 @@ def page_size(self) -> int:
 
     def prepare(self) -> None:
         extra_attrs = get_model_extra_attrs()
-        if extra_attrs is not None:
-            extra_attrs["attention_metadata"] = weakref.ref(self)
-        else:
+        if extra_attrs is None:
             get_global_attrs().attention_metadata = weakref.ref(self)
         # start and end indices of each sequence in the ragged query
         torch.cumsum(self.seq_lens_cuda,
diff --git a/tensorrt_llm/_torch/attention_backend/interface.py b/tensorrt_llm/_torch/attention_backend/interface.py
index 503a0ee2f314..5fa9cc7f3cda 100644
--- a/tensorrt_llm/_torch/attention_backend/interface.py
+++ b/tensorrt_llm/_torch/attention_backend/interface.py
@@ -144,9 +144,9 @@ def on_update(self):
             ).item()
             self._num_generations = self._seq_lens.shape[0] - self.num_contexts
         if self._seq_lens_kv is not None:
-            self._num_tokens = int(self._seq_lens_kv.sum())
+            self._num_tokens = self._seq_lens_kv.sum().item()
         elif self._seq_lens is not None:
-            self._num_tokens = int(self._seq_lens.sum())
+            self._num_tokens = self._seq_lens.sum().item()
 
     @property
     def seq_lens(self) -> Optional[torch.Tensor]:
@@ -296,9 +296,6 @@ def create_cuda_graph_metadata(self,
                 )
 
         cuda_graph_metadata.num_contexts = 0
-        cuda_graph_metadata.max_num_requests = max_batch_size
-        cuda_graph_metadata.max_num_tokens = max_batch_size * (1 +
-                                                               max_draft_tokens)
         cuda_graph_metadata.__post_init__()
         return cuda_graph_metadata
 
diff --git a/tensorrt_llm/_torch/attention_backend/trtllm.py b/tensorrt_llm/_torch/attention_backend/trtllm.py
index ee5b1683052a..04791f9da847 100644
--- a/tensorrt_llm/_torch/attention_backend/trtllm.py
+++ b/tensorrt_llm/_torch/attention_backend/trtllm.py
@@ -1,3 +1,4 @@
+import weakref
 from dataclasses import dataclass, field
 from typing import Optional
 
@@ -7,6 +8,7 @@
 from tensorrt_llm.logger import logger
 from tensorrt_llm.models.modeling_utils import QuantConfig
 
+from ..utils import get_global_attrs, get_model_extra_attrs
 from .interface import (AttentionBackend, AttentionInputType, AttentionMask,
                         AttentionMetadata, KVCacheParams, MLAParams,
                         PositionalEmbeddingParams, PredefinedAttentionMask,
@@ -531,7 +533,10 @@ def __post_init__(self) -> None:
                 )
 
     def prepare(self) -> None:
-
+        extra_attrs = get_model_extra_attrs()
+        # If model extra attrs is set, attention_metadata is setup in executor.
+        if extra_attrs is None:
+            get_global_attrs().attention_metadata = weakref.ref(self)
         if self.kv_cache_manager is None:
             # Convert the attention metadata to a TRT-LLM no cache attention metadata.
             assert self.kv_cache_manager is None, "no cache attention should not have KV cache manager"
@@ -726,7 +731,6 @@ def update_quant_config(self, new_quant_config: Optional[QuantConfig]):
             self.has_fp8_block_wise = self.quant_config.layer_quant_mode.has_fp8_block_scales(
             )
             self.has_nvfp4 = self.quant_config.layer_quant_mode.has_nvfp4()
-            self.has_nvfp4 = self.quant_config.layer_quant_mode.has_nvfp4()
 
     def get_local_layer_idx(self, metadata: TrtllmAttentionMetadata) -> int:
         if metadata.kv_cache_manager is None:
diff --git a/tensorrt_llm/_torch/compilation/patterns/ub_allreduce.py b/tensorrt_llm/_torch/compilation/patterns/ub_allreduce.py
index 87b47eba75d3..b9c49508d7a9 100644
--- a/tensorrt_llm/_torch/compilation/patterns/ub_allreduce.py
+++ b/tensorrt_llm/_torch/compilation/patterns/ub_allreduce.py
@@ -191,8 +191,8 @@ def register_convert_supported_ar_to_ub(custom_pass: PatternMatcherPass):
         fusion = KeywordArg('fusion_op')
         trtllm_allreduce_default = CallFunction(
             torch.ops.trtllm.allreduce.default, input_node,
-            KeywordArg('residual_in'), KeywordArg('gamma'), Ignored(),
-            Ignored(), Ignored(), mapping.tp_group, strategy, fusion,
+            KeywordArg('residual_in'), KeywordArg('gamma'), KeywordArg('scale'),
+            None, Ignored(), mapping.tp_group, strategy, fusion,
             KeywordArg('eps'))
         convert_pattern = MultiOutputPattern([trtllm_allreduce_default])
 
@@ -200,6 +200,7 @@ def empty_convert_supported_ar_to_ub(
             input: torch.Tensor,
             residual_in: torch.Tensor,
             gamma: torch.Tensor,
+            scale: torch.Tensor,
             fusion_op: int,
             eps: float,
         ):
@@ -209,12 +210,13 @@ def target_convert_supported_ar_to_ub(
             input: torch.Tensor,
             residual_in: torch.Tensor,
             gamma: torch.Tensor,
+            scale: torch.Tensor,
             fusion_op: int,
             eps: float,
         ):
             input = torch.ops.trtllm.copy_to_userbuffers(input)
             all_reduce_output = torch.ops.trtllm.allreduce(
-                input, residual_in, gamma, None, None, None, mapping.tp_group,
+                input, residual_in, gamma, scale, None, None, mapping.tp_group,
                 int(AllReduceStrategy.UB), fusion_op, eps)
             finalize_output = torch.ops.trtllm.userbuffers_allreduce_finalize(
                 all_reduce_output[-1], False)
diff --git a/tensorrt_llm/_torch/custom_ops/cpp_custom_ops.py b/tensorrt_llm/_torch/custom_ops/cpp_custom_ops.py
index 6f913da2a1f9..38eeb8b20a3b 100644
--- a/tensorrt_llm/_torch/custom_ops/cpp_custom_ops.py
+++ b/tensorrt_llm/_torch/custom_ops/cpp_custom_ops.py
@@ -4,6 +4,8 @@
 
 import tensorrt_llm.quantization.utils.fp4_utils as fp4_utils
 
+from ..._utils import get_sm_version
+
 
 def _register_fake():
 
@@ -123,7 +125,7 @@ def _(input, force_applying_finalize):
     def _(a, b, a_scale, b_scale):
         m = a.shape[0]
         n = b.shape[0]
-        return a.new_empty((m, n))
+        return a.new_empty((m, n), dtype=torch.bfloat16)
 
     @torch.library.register_fake(
         "tensorrt_llm::static_quantize_e4m3_per_tensor")
@@ -284,3 +286,24 @@ def _(
         weight_bias: float,
     ) -> List[torch.Tensor]:
         return outputs
+
+    @torch.library.register_fake(
+        "trtllm::mtp_sampling_and_accepted_draft_tokens_op")
+    def _(logits: torch.Tensor, draft_tokens: torch.Tensor,
+          target_tokens: torch.Tensor, num_mtp_modules: int, batch_size: int,
+          num_context_request: int, vocab_size: int):
+        return logits.new_empty((batch_size, num_mtp_modules + 1),
+                                dtype=torch.int32), logits.new_empty(
+                                    (batch_size, ), dtype=torch.int32)
+
+    @torch.library.register_fake("trtllm::fp8_quantize_1x128")
+    def _(input: torch.Tensor):
+        pad_m = fp4_utils.pad_up(input.shape[0], 4)
+        blocked_n = (input.shape[1] + 127) // 128
+        if get_sm_version() >= 100:
+            sz = (blocked_n, input.shape[0])
+        else:
+            sz = (fp4_utils.pad_up(pad_m * blocked_n * 4, 128) // 4, )
+        return torch.empty_like(input,
+                                dtype=torch.float8_e4m3fn), input.new_empty(
+                                    sz, dtype=torch.float)
diff --git a/tensorrt_llm/_torch/model_config.py b/tensorrt_llm/_torch/model_config.py
index 4412a9a6c0db..288e80dc1c60 100644
--- a/tensorrt_llm/_torch/model_config.py
+++ b/tensorrt_llm/_torch/model_config.py
@@ -32,6 +32,8 @@ class ModelConfig(Generic[TConfig]):
     attn_backend: str = 'TRTLLM'
     moe_backend: str = 'CUTLASS'  # options can be CUTLASS, TRTLLM
 
+    extra_attrs: Dict = field(default_factory=dict, repr=False, init=False)
+
     def __post_init__(self):
         if self.pretrained_config and hasattr(self.pretrained_config,
                                               "architectures"):
diff --git a/tensorrt_llm/_torch/models/modeling_deepseekv3.py b/tensorrt_llm/_torch/models/modeling_deepseekv3.py
index 687b5ab5ad01..ef32b45a0fa1 100644
--- a/tensorrt_llm/_torch/models/modeling_deepseekv3.py
+++ b/tensorrt_llm/_torch/models/modeling_deepseekv3.py
@@ -633,19 +633,19 @@ def _compute_mlp_tp_size(self, intermediate_size: int,
         """
 
         assert intermediate_size % block_size == 0, "intermediate_size must be divisible by block_size."
-
         if self.enable_attention_dp:
             # If using attention DP, the MLP also uses DP instead of TP.
             mlp_tp_size = 1
         else:
             # The two math.gcd operations ensure that mlp_tp_size falls in the candidate TP sizes.
-            mlp_tp_size = math.gcd(
-                math.gcd(
-                    intermediate_size // block_size,
-                    self.mapping.tp_size,
-                ),
-                self.mapping.gpus_per_node,  # Avoid costly inter-node TP
+            tp = math.gcd(
+                intermediate_size // block_size,
+                self.mapping.tp_size,
             )
+            mlp_tp_size = math.gcd(
+                tp,
+                self.mapping.gpus_per_node,
+            ) if tp > self.mapping.gpus_per_node else tp  # Avoid costly inter-node TP
         return mlp_tp_size
 
     def _enable_min_latency_mode(self, num_tokens: int):
diff --git a/tensorrt_llm/_torch/modules/attention.py b/tensorrt_llm/_torch/modules/attention.py
index 9905cc20722d..3a82d883d1f6 100644
--- a/tensorrt_llm/_torch/modules/attention.py
+++ b/tensorrt_llm/_torch/modules/attention.py
@@ -1,4 +1,5 @@
 import math
+import weakref
 from enum import IntEnum
 from typing import Optional, cast
 
@@ -15,6 +16,7 @@
 from ..distributed import AllReduceParams
 from ..model_config import ModelConfig
 from ..peft.lora.layer import LoraLayer, LoraModuleType
+from ..utils import get_model_extra_attrs
 from .linear import Linear, TensorParallelMode, WeightMode, WeightsLoadingConfig
 from .multi_stream_utils import maybe_execute_in_parallel
 from .rms_norm import RMSNorm
@@ -277,6 +279,47 @@ def apply_qk_norm(self, q, k):
             "Please override the `apply_qk_norm` method in the subclass.")
 
 
+def extract_extra_attrs(layer_idx: str):
+    extra_attrs = get_model_extra_attrs()
+    assert extra_attrs is not None, "Model extra attrs is not set"
+
+    metadata_ref = extra_attrs.get("attention_metadata", None)
+    assert metadata_ref is not None, "Attention metadata is not set"
+    metadata = metadata_ref()
+    assert isinstance(
+        metadata,
+        TrtllmAttentionMetadata,
+    )
+
+    mla_layers = extra_attrs.get("mla_layers", None)
+    assert mla_layers is not None, "MLA layers is not registered"
+    mla_layer_ref = mla_layers.get(layer_idx, None)
+    assert mla_layer_ref is not None, f"Cannot find MLA layer for layer {layer_idx}"
+    mla_layer = mla_layer_ref()
+    assert isinstance(
+        mla_layer,
+        MLA), "MLA layer must be a subclass of MLA or an instance of MLA"
+
+    return metadata, mla_layer
+
+
+@torch.library.custom_op("trtllm::mla_custom_op", mutates_args=())
+def mla_custom_op(
+    position_ids: Optional[torch.Tensor],
+    hidden_states: torch.Tensor,
+    layer_idx: str,
+) -> torch.Tensor:
+    metadata, mla_layer = extract_extra_attrs(layer_idx)
+
+    return mla_layer.forward_impl(position_ids, hidden_states, metadata)
+
+
+@mla_custom_op.register_fake
+def _(position_ids, hidden_states, layer_idx):
+    _, mla_layer = extract_extra_attrs(layer_idx)
+    return mla_layer.forward_impl_fake(hidden_states)
+
+
 class MLA(nn.Module):
 
     def __init__(
@@ -324,6 +367,7 @@ def __init__(
         """
         super().__init__()
         self.layer_idx = layer_idx
+        self.layer_idx_str = str(layer_idx)
         self.dtype = dtype
 
         self.hidden_size = hidden_size
@@ -351,6 +395,14 @@ def __init__(
 
         assert pos_embd_params is not None, "pos_embd_params must be provided in MLA"
 
+        self.register_to_config = False
+        if config is not None:
+            if "mla_layers" not in config.extra_attrs:
+                config.extra_attrs["mla_layers"] = {}
+            config.extra_attrs["mla_layers"][self.layer_idx_str] = weakref.ref(
+                self)
+            self.register_to_config = True
+
         # tensor parallel
         config = config or ModelConfig()
         tp_size = config.mapping.tp_size
@@ -584,12 +636,17 @@ def apply_rope(
                                                    self.qk_rope_head_dim)
         return k_pe
 
-    def forward(
+    def forward_impl_fake(self, hidden_states: torch.Tensor):
+        num_tokens = hidden_states.shape[0]
+        hidden_size = self.o_proj.in_features
+        return hidden_states.new_empty([num_tokens, hidden_size],
+                                       dtype=hidden_states.dtype)
+
+    def forward_impl(
         self,
-        position_ids: Optional[torch.LongTensor],
+        position_ids: Optional[torch.Tensor],
         hidden_states: torch.Tensor,
         attn_metadata: AttentionMetadata,
-        all_reduce_params: Optional[AllReduceParams] = None,
     ) -> torch.Tensor:
         """
         Forward pass for the MLA module.
@@ -692,8 +749,6 @@ def forward(
         else:
             attn_output = attn_output_gen
 
-        attn_output = self.o_proj(attn_output,
-                                  all_reduce_params=all_reduce_params)
         return attn_output
 
     def _maybe_concat_qkv(self, q, k, v):
@@ -987,3 +1042,20 @@ def forward_generation(
 
         # [seq, num_heads * v_head_dim]
         return attn_output.flatten(1, 2)
+
+    def forward(
+        self,
+        position_ids: Optional[torch.Tensor],
+        hidden_states: torch.Tensor,
+        attn_metadata: AttentionMetadata,
+        all_reduce_params: Optional[AllReduceParams] = None,
+    ) -> torch.Tensor:
+        if self.register_to_config:
+            attn_output = torch.ops.trtllm.mla_custom_op(
+                position_ids, hidden_states, self.layer_idx_str)
+        else:
+            attn_output = self.forward_impl(position_ids, hidden_states,
+                                            attn_metadata)
+        attn_output = self.o_proj(attn_output,
+                                  all_reduce_params=all_reduce_params)
+        return attn_output
diff --git a/tensorrt_llm/_torch/pyexecutor/model_engine.py b/tensorrt_llm/_torch/pyexecutor/model_engine.py
index 6fb7cdf2cf4c..73bf0cd571c3 100644
--- a/tensorrt_llm/_torch/pyexecutor/model_engine.py
+++ b/tensorrt_llm/_torch/pyexecutor/model_engine.py
@@ -8,6 +8,7 @@
 import multiprocessing
 import os
 import traceback
+import weakref
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from typing import Any, Dict, List, Optional, Tuple
@@ -44,7 +45,8 @@
 from ..models.modeling_utils import (DecoderModelForCausalLM, MetaInitMode,
                                      timing)
 from ..speculative import SpecConfig, SpecMetadata, get_spec_metadata
-from ..utils import set_torch_compiling, with_model_extra_attrs
+from ..utils import (get_model_extra_attrs, set_torch_compiling,
+                     with_model_extra_attrs)
 from .config import LoadFormat, PyTorchConfig
 from .config_utils import is_mla
 from .cuda_graph_runner import DecodingCUDAGraphRunner
@@ -586,6 +588,8 @@ def disable_optimization(backend: Backend):
 
                 # Disable cuda graph capture here so that we can properly capture it later
                 with no_cuda_graph():
+                    available_tokens = kv_cache_manager.get_num_available_tokens(
+                        self.max_draft_len)
                     warmup_batch_size = [1, self.batch_size // 2]
                     if self.batch_size < 2:
                         warmup_batch_size = [1]
@@ -593,7 +597,7 @@ def disable_optimization(backend: Backend):
                         for num_tokens_per_request in [
                                 1,
                                 min(self.max_num_tokens // max(bs, 1),
-                                    self.max_seq_len - 1)
+                                    min(available_tokens, self.max_seq_len - 1))
                         ]:
                             with release_batch(
                                     get_torch_compile_warmup_request(
@@ -614,8 +618,11 @@ def disable_optimization(backend: Backend):
 
             if self.pytorch_backend_config.autotuner_enabled:
                 with no_cuda_graph(), autotune():
-                    num_tokens_per_request = min(self.max_seq_len - 1,
-                                                 self.max_num_tokens)
+                    available_tokens = kv_cache_manager.get_num_available_tokens(
+                        self.max_draft_len)
+                    num_tokens_per_request = min(
+                        min(available_tokens, self.max_seq_len - 1),
+                        self.max_num_tokens)
                     with release_batch(
                             get_torch_compile_warmup_request(
                                 1, num_tokens_per_request)) as batch:
@@ -1909,6 +1916,11 @@ def forward(self,
             return outputs
 
     def model_forward(self, **kwargs):
+        attrs = get_model_extra_attrs()
+        assert attrs is not None, "Model extra attrs is not set"
+        attrs["attention_metadata"] = weakref.ref(kwargs['attn_metadata'])
+        attrs.update(self.model.model_config.extra_attrs)
+
         if is_trace_enabled("TLLM_TRACE_MODEL_FORWARD"):
             return trace_func(self.model.forward)(**kwargs)
         else:
diff --git a/tensorrt_llm/_torch/speculative/mtp.py b/tensorrt_llm/_torch/speculative/mtp.py
index 463074342437..144633f4c409 100644
--- a/tensorrt_llm/_torch/speculative/mtp.py
+++ b/tensorrt_llm/_torch/speculative/mtp.py
@@ -731,7 +731,6 @@ def sample_and_accept_draft_tokens(
         num_accepted_tokens = torch.ones(batch_size,
                                          dtype=torch.int,
                                          device=logits.device)
-
         if self.spec_config.use_relaxed_acceptance_for_thinking:
             mtp_relaxed_delta_pool = spec_metadata.mtp_hidden_states_manager.mtp_relaxed_delta_pool
 
@@ -793,8 +792,7 @@ def sample_and_accept_draft_tokens(
                                                   device=logits.device)
                 accepted_tokens, num_accepted_tokens = torch.ops.trtllm.mtp_sampling_and_accepted_draft_tokens_op(
                     logits, spec_metadata.draft_tokens, target_tokens_cache,
-                    accepted_tokens, num_accepted_tokens, mtp_num_modules,
-                    batch_size, num_contexts, logits.shape[-1])
+                    mtp_num_modules, batch_size, num_contexts, logits.shape[-1])
             else:
                 # Do greedy sampling for the input logits
                 target_tokens = torch.argmax(logits, dim=-1)
diff --git a/tests/integration/defs/.test_durations b/tests/integration/defs/.test_durations
index 6415ca03b4d6..1b6d8f8aff5f 100644
--- a/tests/integration/defs/.test_durations
+++ b/tests/integration/defs/.test_durations
@@ -131,8 +131,8 @@
    "examples/test_multimodal.py::test_llm_multimodal_general[llava-v1.6-mistral-7b-hf-vision-trtllm-pp:1-tp:1-float16-bs:1-cpp_e2e:False-nb:1]": 306.38610201328993,
    "examples/test_prompt_lookup.py::test_llm_prompt_lookup_1gpu[streaming-gpt2-use_cpp_session-use_tokens-max_matching_ngram_size_2-prompt_lookup_num_tokens_8-float16-bs2]": 195.90045699477196,
    "test_unittests.py::test_unittests_v2[unittest/trt/model/test_gpt.py -k \"partition2\"]": 357.6496359631419,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]": 413.903915906325,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]": 143.841789112892,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 413.903915906325,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]": 143.841789112892,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_bfloat16[attn_backend=FLASHINFER-torch_compile=False]": 307.12596721109,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_bfloat16[attn_backend=TRTLLM-torch_compile=True]": 166.85348949534819,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=False-attn_backend=FLASHINFER-torch_compile=True]": 226.39608797896653,
@@ -228,10 +228,10 @@
    "test_e2e.py::test_llmapi_server_example": 112.925546400249,
    "test_unittests.py::test_unittests_v2[unittest/trt/functional]": 778.6451135131065,
    "test_unittests.py::test_unittests_v2[unittest/trt/model/test_mamba.py]": 76.84791256207973,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]": 506.1045090719126,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]": 184.20976317999884,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]": 202.37037238897756,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]": 246.64391099987552,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 506.1045090719126,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]": 184.20976317999884,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 202.37037238897756,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]": 246.64391099987552,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=False-attn_backend=TRTLLM-torch_compile=True]": 313.69273760309443,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=True-attn_backend=FLASHINFER-torch_compile=False]": 409.8932851999998,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=True-attn_backend=FLASHINFER-torch_compile=True]": 344.8807112099603,
@@ -284,13 +284,13 @@
    "disaggregated/test_disaggregated.py::test_disaggregated_overlap[TinyLlama-1.1B-Chat-v1.0]": 98.97588296607137,
    "disaggregated/test_disaggregated.py::test_disaggregated_single_gpu_with_mpirun[TinyLlama-1.1B-Chat-v1.0]": 67.9668476767838,
    "test_unittests.py::test_unittests_v2[unittest/_torch/test_attention_mla.py]": 26.32902159006335,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]": 591.2785023800097,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]": 306.84709841990843,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]": 220.57452515885234,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]": 202.22269394202158,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]": 165.08514453098178,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]": 252.70569713797886,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]": 85.24235329206567,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 591.2785023800097,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]": 306.84709841990843,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 220.57452515885234,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]": 202.22269394202158,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]": 165.08514453098178,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]": 252.70569713797886,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]": 85.24235329206567,
    "test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-FP8-llama-3.1-model/Llama-3.1-8B-Instruct-FP8]": 81.43792725296225,
    "test_e2e.py::test_ptp_quickstart_advanced_eagle3[Llama-3.1-8b-Instruct-llama-3.1-model/Llama-3.1-8B-Instruct-EAGLE3-LLaMA3.1-Instruct-8B]": 109.26379436196294,
    "test_e2e.py::test_ptp_quickstart_advanced_mixed_precision": 80.88908524392173,
@@ -308,11 +308,11 @@
    "test_e2e.py::test_llmapi_load_engine_from_build_command[llama-llama-models/llama-7b-hf]": 200.82293555140495,
    "test_unittests.py::test_unittests_v2[unittest/trt/model/test_llama.py]": 1494.1103300452232,
    "test_unittests.py::test_unittests_v2[unittest/trt/attention/test_gpt_attention.py -k \"partition0\"]": 77.31474154582247,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]": 295.3527018489549,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]": 143.84012729604729,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]": 107.58471493399702,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]": 205.7252635700861,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]": 113.82226522010751,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 295.3527018489549,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]": 143.84012729604729,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]": 107.58471493399702,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]": 205.7252635700861,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 113.82226522010751,
    "examples/test_llama.py::test_llm_llama_1gpu[llama-3.1-8b-instruct-hf-fp8-enable_fp8-float16-summarization-nb:1]": 853.2910006027669,
    "test_e2e.py::test_openai_chat_example": 876.1966922096908,
    "test_e2e.py::test_trtllm_serve_example": 200.09309104084969,
@@ -338,9 +338,9 @@
    "accuracy/test_cli_flow.py::TestLlama3_2_1B::test_smooth_quant_ootb_manage_weights": 216.66169160604477,
    "accuracy/test_cli_flow.py::TestTinyLlama1_1BChat::test_weight_only_manage_weights[int4]": 161.57166086137295,
    "test_unittests.py::test_unittests_v2[unittest/llmapi/test_llm.py -m \"not part0\"]": 1883.5484512336552,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]": 89.92349556891713,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[attention_dp-cuda_graph-overlap_scheduler]": 175.661773331929,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]": 90.21807348495349,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 89.92349556891713,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[attention_dp-cuda_graph-overlap_scheduler-torch_compile=False]": 175.661773331929,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 90.21807348495349,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8B::test_nvfp4": 56.31924073398113,
    "test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-NVFP4-nvfp4-quantized/Meta-Llama-3.1-8B]": 56.05445321695879,
    "test_e2e.py::test_trtllm_bench_pytorch_backend_sanity[meta-llama/Llama-3.1-8B-llama-3.1-8b-False-False]": 114.17938271397725,
@@ -362,10 +362,10 @@
    "examples/test_multimodal.py::test_llm_fp8_multimodal_general[fp8-fp8-cnn_dailymail-Qwen2-VL-7B-Instruct-pp:1-tp:1-bfloat16-bs:1-cpp_e2e:False]": 332.0248579243198,
    "test_e2e.py::test_mistral_large_hidden_vocab_size": 81.36711680702865,
    "test_e2e.py::test_trtllm_bench_iteration_log[TRT-non-streaming-meta-llama/Llama-3.1-8B-llama-3.1-model/Meta-Llama-3.1-8B]": 285.3362849447876,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]": 647.6109309499152,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[-attention_dp-cuda_graph-overlap_scheduler]": 326.1317654890008,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]": 226.01353620411828,
-   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-attention_dp-cuda_graph-overlap_scheduler]": 336.02580665098503,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]": 647.6109309499152,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[-attention_dp-cuda_graph-overlap_scheduler-torch_compile=False]": 326.1317654890008,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]": 226.01353620411828,
+   "accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-attention_dp-cuda_graph-overlap_scheduler-torch_compile=False]": 336.02580665098503,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_bfloat16[attn_backend=FLASHINFER-torch_compile=True]": 443.91388061689213,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_bfloat16[attn_backend=TRTLLM-torch_compile=False]": 191.10617867391557,
    "accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=False-attn_backend=FLASHINFER-torch_compile=False]": 237.24446990108117,
diff --git a/tests/integration/defs/accuracy/test_llm_api_pytorch.py b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
index 539f46850c2e..052a1e27f933 100644
--- a/tests/integration/defs/accuracy/test_llm_api_pytorch.py
+++ b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
@@ -75,6 +75,7 @@ def test_chunked_prefill(self, attn_backend):
     def test_bfloat16(self, attn_backend, torch_compile):
         pytorch_config = PyTorchConfig(
             torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True,
             cuda_graph_padding_enabled=torch_compile,
             cuda_graph_batch_sizes=[4],
             attn_backend=attn_backend,
@@ -100,6 +101,7 @@ def test_bfloat16_4gpus(self, tp_size, pp_size, attn_backend,
                 "discarded at graph breaks.")
         pytorch_config = PyTorchConfig(
             torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True,
             cuda_graph_padding_enabled=torch_compile,
             cuda_graph_batch_sizes=[4],
             attn_backend=attn_backend,
@@ -123,6 +125,7 @@ def test_fp8(self, fp8kv, attn_backend, torch_compile):
         quant_config = QuantConfig(QuantAlgo.FP8)
         pytorch_config = PyTorchConfig(
             torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True,
             cuda_graph_padding_enabled=torch_compile,
             cuda_graph_batch_sizes=[4],
             attn_backend=attn_backend,
@@ -160,6 +163,7 @@ def test_fp8_4gpus(self, tp_size, pp_size, fp8kv, attn_backend,
         quant_config = QuantConfig(QuantAlgo.FP8)
         pytorch_config = PyTorchConfig(
             torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True,
             cuda_graph_padding_enabled=torch_compile,
             cuda_graph_batch_sizes=[4],
             attn_backend=attn_backend,
@@ -344,20 +348,27 @@ class TestDeepSeekV3Lite(LlmapiAccuracyTestHarness):
     MODEL_PATH = f"{llm_models_root()}/DeepSeek-V3-Lite/bf16"
 
     @pytest.mark.skip_less_device_memory(60000)
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False), (True, False, False),
                            (False, True, False), (False, False, True),
-                           (True, True, True)])
+                           (False, True, True), (True, True, True)])
     # Only Hopper and Blackwell MLA kernel supports MTP
     @parametrize_with_ids("mtp_nextn",
                           [0, pytest.param(2, marks=skip_pre_hopper)])
     def test_bfloat16(self, mtp_nextn, attention_dp, cuda_graph,
-                      overlap_scheduler):
+                      overlap_scheduler, torch_compile):
+        if torch_compile and mtp_nextn > 0:
+            pytest.skip("https://nvbugs/5252313")
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
         # OOM on H100 with default free_gpu_memory_fraction=0.9
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.6)
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
         mtp_config = None
         if mtp_nextn > 0:
             mtp_config = MTPDecodingConfig(num_nextn_predict_layers=mtp_nextn)
@@ -373,10 +384,11 @@ def test_bfloat16(self, mtp_nextn, attention_dp, cuda_graph,
             task.evaluate(llm)
 
     @pytest.mark.skip_less_device(4)
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False), (True, False, False),
                            (False, True, False), (False, False, True),
-                           (True, True, True)])
+                           (False, True, True), (True, True, True)])
     # Only Hopper and Blackwell MLA kernel supports MTP
     @parametrize_with_ids("mtp_nextn",
                           [0, pytest.param(2, marks=skip_pre_hopper)])
@@ -384,12 +396,21 @@ def test_bfloat16(self, mtp_nextn, attention_dp, cuda_graph,
                                                          (2, 2, 1), (1, 4, 1)],
                              ids=["tp4", "ep4", "tp2pp2", "pp4"])
     def test_bfloat16_4gpus(self, tp_size, pp_size, ep_size, mtp_nextn,
-                            attention_dp, cuda_graph, overlap_scheduler):
+                            attention_dp, cuda_graph, overlap_scheduler,
+                            torch_compile):
+        if torch_compile and mtp_nextn > 0:
+            pytest.skip("https://nvbugs/5252313")
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
+        if torch_compile and pp_size > 1:
+            pytest.skip("PP with torch.compile is not supported yet.")
         # OOM on H100 with default free_gpu_memory_fraction=0.9
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.7)
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
         mtp_config = None
         if mtp_nextn > 0:
             mtp_config = MTPDecodingConfig(num_nextn_predict_layers=mtp_nextn)
@@ -408,22 +429,29 @@ def test_bfloat16_4gpus(self, tp_size, pp_size, ep_size, mtp_nextn,
             task.evaluate(llm)
 
     @pytest.mark.skip_device_not_contain(["H100", "H200"])
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("fp8kv,attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False, False),
                            (True, False, False, False),
                            (False, True, False, False),
                            (False, False, True, False),
                            (False, False, False, True),
-                           (True, True, True, True)])
+                           (True, False, True, True), (True, True, True, True)])
     @parametrize_with_ids("mtp_nextn", [0, 2])
     def test_fp8_block_scales(self, mtp_nextn, fp8kv, attention_dp, cuda_graph,
-                              overlap_scheduler):
+                              overlap_scheduler, torch_compile):
+        if torch_compile and mtp_nextn > 0:
+            pytest.skip("https://nvbugs/5252313")
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
         # OOM on H100 with default free_gpu_memory_fraction=0.9
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.8,
                                         enable_block_reuse=not fp8kv)
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
 
         quant_config = QuantConfig()
         quant_config.quant_algo = QuantAlgo.FP8_BLOCK_SCALES
@@ -474,26 +502,36 @@ def test_fp8_block_scales_cuda_graph_padding(self):
 
     @pytest.mark.skip_less_device(4)
     @pytest.mark.skip_device_not_contain(["H100", "H200"])
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("fp8kv,attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False, False),
                            (True, False, False, False),
                            (False, True, False, False),
                            (False, False, True, False),
                            (False, False, False, True),
-                           (False, True, True, True), (True, True, True, True)])
+                           (False, True, True, True), (True, False, True, True),
+                           (True, True, True, True)])
     @parametrize_with_ids("mtp_nextn", [0, 2])
     @pytest.mark.parametrize("tp_size,pp_size,ep_size", [(4, 1, 1), (4, 1, 4),
                                                          (2, 2, 1), (1, 4, 1)],
                              ids=["tp4", "ep4", "tp2pp2", "pp4"])
     def test_fp8_block_scales_4gpus(self, tp_size, pp_size, ep_size, mtp_nextn,
                                     fp8kv, attention_dp, cuda_graph,
-                                    overlap_scheduler):
+                                    overlap_scheduler, torch_compile):
+        if torch_compile and mtp_nextn > 0:
+            pytest.skip("https://nvbugs/5252313")
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
+        if torch_compile and pp_size > 1:
+            pytest.skip("PP with torch.compile is not supported yet.")
         # OOM on H100 with default free_gpu_memory_fraction=0.9
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.8,
                                         enable_block_reuse=not fp8kv)
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
 
         quant_config = QuantConfig()
         quant_config.quant_algo = QuantAlgo.FP8_BLOCK_SCALES
@@ -528,19 +566,26 @@ def test_fp8_block_scales_4gpus(self, tp_size, pp_size, ep_size, mtp_nextn,
             task.evaluate(llm)
 
     @skip_pre_blackwell
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("fp8kv,attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False, False),
                            (True, False, False, False),
                            (False, True, False, False),
                            (False, False, True, False),
                            (False, False, False, True),
-                           (True, True, True, True)])
-    def test_nvfp4(self, fp8kv, attention_dp, cuda_graph, overlap_scheduler):
+                           (True, False, True, True), (True, True, True, True)])
+    def test_nvfp4(self, fp8kv, attention_dp, cuda_graph, overlap_scheduler,
+                   torch_compile):
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.9,
                                         enable_block_reuse=not fp8kv)
+
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
 
         quant_config = QuantConfig()
         quant_config.quant_algo = QuantAlgo.NVFP4
@@ -568,23 +613,31 @@ def test_nvfp4(self, fp8kv, attention_dp, cuda_graph, overlap_scheduler):
 
     @pytest.mark.skip_less_device(4)
     @skip_pre_blackwell
+    @parametrize_with_ids("torch_compile", [False, True])
     @parametrize_with_ids("fp8kv,attention_dp,cuda_graph,overlap_scheduler",
                           [(False, False, False, False),
                            (True, False, False, False),
                            (False, True, False, False),
                            (False, False, True, False),
                            (False, False, False, True),
-                           (True, True, True, True)])
+                           (True, False, True, True), (True, True, True, True)])
     @pytest.mark.parametrize("tp_size,pp_size,ep_size", [(4, 1, 1), (4, 1, 4),
                                                          (2, 2, 1), (1, 4, 1)],
                              ids=["tp4", "ep4", "tp2pp2", "pp4"])
     def test_nvfp4_4gpus(self, fp8kv, attention_dp, cuda_graph,
-                         overlap_scheduler, tp_size, pp_size, ep_size):
+                         overlap_scheduler, tp_size, pp_size, ep_size,
+                         torch_compile):
+        if torch_compile and attention_dp:
+            pytest.skip("https://nvbugs/5252559")
+        if torch_compile and pp_size > 1:
+            pytest.skip("PP with torch.compile is not supported yet.")
         kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.9,
                                         enable_block_reuse=not fp8kv)
         pytorch_config = PyTorchConfig(
             disable_overlap_scheduler=not overlap_scheduler,
-            use_cuda_graph=cuda_graph)
+            use_cuda_graph=cuda_graph,
+            torch_compile_enabled=torch_compile,
+            torch_compile_fullgraph=True)
 
         quant_config = QuantConfig()
         quant_config.quant_algo = QuantAlgo.NVFP4
diff --git a/tests/integration/test_lists/qa/examples_test_list.txt b/tests/integration/test_lists/qa/examples_test_list.txt
index e3e651b8fcfc..adb9a0b15c56 100644
--- a/tests/integration/test_lists/qa/examples_test_list.txt
+++ b/tests/integration/test_lists/qa/examples_test_list.txt
@@ -436,9 +436,9 @@ accuracy/test_llm_api_pytorch.py::TestLlama4ScoutInstruct::test_auto_dtype[tp8ep
 accuracy/test_llm_api_pytorch.py::TestLlama4ScoutInstruct::test_auto_dtype[tp8ep8-cuda_graph=True]
 accuracy/test_llm_api_pytorch.py::TestMixtral8x7B::test_fp8_tp2
 accuracy/test_llm_api_pytorch.py::TestMixtral8x7B::test_nvfp4_tp2
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
 accuracy/test_llm_api_pytorch.py::TestMinitron4BBaseInstruct::test_fp8_prequantized
 accuracy/test_llm_api_pytorch.py::TestNemotronNas::test_auto_dtype_tp8
 accuracy/test_llm_api_pytorch.py::TestNemotronSuper::test_auto_dtype_tp2
diff --git a/tests/integration/test_lists/qa/llm_release_rtx_pro_6000.txt b/tests/integration/test_lists/qa/llm_release_rtx_pro_6000.txt
index 3066fa35c6a6..5a388b5f80bc 100644
--- a/tests/integration/test_lists/qa/llm_release_rtx_pro_6000.txt
+++ b/tests/integration/test_lists/qa/llm_release_rtx_pro_6000.txt
@@ -1,22 +1,22 @@
 accuracy/test_cli_flow.py::TestMixtral8x7B::test_fp8_tp2pp2
 accuracy/test_cli_flow.py::TestMixtral8x7B::test_fp8_tp2pp2_manage_weights
 accuracy/test_cli_flow.py::TestMixtral8x7B::test_nvfp4_prequantized
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
 accuracy/test_llm_api_pytorch.py::TestLlama3_1_8B::test_nvfp4
 test_e2e.py::test_ptp_quickstart_advanced_mixed_precision
 test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-BF16-llama-3.1-model/Meta-Llama-3.1-8B]
diff --git a/tests/integration/test_lists/qa/llm_sanity_test.txt b/tests/integration/test_lists/qa/llm_sanity_test.txt
index 7a9d4743ccd2..ef6fc3ba6072 100644
--- a/tests/integration/test_lists/qa/llm_sanity_test.txt
+++ b/tests/integration/test_lists/qa/llm_sanity_test.txt
@@ -136,9 +136,9 @@ accuracy/test_llm_api_pytorch.py::TestMixtral8x7B::test_nvfp4_tp2
 accuracy/test_llm_api_pytorch.py::TestNemotronNas::test_auto_dtype_tp8
 accuracy/test_llm_api_pytorch.py::TestNemotronSuper::test_auto_dtype_tp2
 accuracy/test_llm_api_pytorch.py::TestNemotronNano::test_auto_dtype
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
 
 # Pivot to Pytorch test cases.
 test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-BF16-llama-3.1-model/Meta-Llama-3.1-8B]
diff --git a/tests/integration/test_lists/test-db/l0_b200.yml b/tests/integration/test_lists/test-db/l0_b200.yml
index 9ac754e11fe2..3d394e45bc6f 100644
--- a/tests/integration/test_lists/test-db/l0_b200.yml
+++ b/tests/integration/test_lists/test-db/l0_b200.yml
@@ -15,22 +15,29 @@ l0_b200:
   tests:
   # ------------- PyTorch tests ---------------
   - accuracy/test_llm_api_pytorch.py::TestLlama3_1_8B::test_nvfp4
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_no_kv_cache_reuse[quant_dtype=none-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_no_kv_cache_reuse[quant_dtype=nvfp4-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[latency]
diff --git a/tests/integration/test_lists/test-db/l0_dgx_h100.yml b/tests/integration/test_lists/test-db/l0_dgx_h100.yml
index f8ba95fb838d..a35aed1219a5 100644
--- a/tests/integration/test_lists/test-db/l0_dgx_h100.yml
+++ b/tests/integration/test_lists/test-db/l0_dgx_h100.yml
@@ -52,44 +52,53 @@ l0_dgx_h100:
       auto_trigger: deepseek
   tests:
   - unittest/_torch/multi_gpu_modeling -k "deepseek"
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[pp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[pp4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp2pp2-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[pp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[pp4-mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[pp4-mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   - disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8[DeepSeek-V3-Lite-fp8]
   - disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8_ucx[DeepSeek-V3-Lite-fp8]
   - disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8_attention_dp[DeepSeek-V3-Lite-fp8]
@@ -179,38 +188,44 @@ l0_dgx_h100:
       auto_trigger: others
   tests:
   # ------------- PyTorch tests ---------------
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[pp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[pp4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp2pp2-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[pp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[pp4-mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[pp4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   - unittest/_torch/auto_deploy/integration/test_ad_build.py
   - unittest/_torch/auto_deploy/integration/test_lm_eval.py
   - accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_bfloat16_4gpus[tp4-attn_backend=FLASHINFER-torch_compile=False]
diff --git a/tests/integration/test_lists/test-db/l0_dgx_h200.yml b/tests/integration/test_lists/test-db/l0_dgx_h200.yml
index eb338f06dec1..d3fb5bec0641 100644
--- a/tests/integration/test_lists/test-db/l0_dgx_h200.yml
+++ b/tests/integration/test_lists/test-db/l0_dgx_h200.yml
@@ -14,7 +14,7 @@ l0_dgx_h200:
       backend: pytorch
   tests:
   # ------------- PyTorch tests ---------------
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   # - accuracy/test_llm_api_pytorch.py::TestDeepSeekR1::test_fp8_blockscale[throughput] # OOM
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekR1::test_fp8_blockscale[latency] # 1h
   - unittest/_torch/multi_gpu_modeling/test_llama4.py::test_llama4[pp1-ep1-enable_graph-tp8-trtllm-scout]
diff --git a/tests/integration/test_lists/test-db/l0_h100.yml b/tests/integration/test_lists/test-db/l0_h100.yml
index 83a655429094..8f76db4df670 100644
--- a/tests/integration/test_lists/test-db/l0_h100.yml
+++ b/tests/integration/test_lists/test-db/l0_h100.yml
@@ -32,18 +32,22 @@ l0_h100:
   - accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=True-attn_backend=TRTLLM-torch_compile=True]
   - accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=True-attn_backend=FLASHINFER-torch_compile=False]
   - accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8[fp8kv=True-attn_backend=FLASHINFER-torch_compile=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=True-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_no_kv_cache_reuse[quant_dtype=fp8-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_fp8_block_scales[latency]
   - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8[latency]
@@ -178,16 +182,20 @@ l0_h100:
       backend: pytorch
   tests:
   # ------------- PyTorch tests ---------------
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
-  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=True-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=True]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False]
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_no_kv_cache_reuse[quant_dtype=none-mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8_block_scales[latency]
 - condition:
diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt
index e5fc5f81be43..48b723bb3f20 100644
--- a/tests/integration/test_lists/waives.txt
+++ b/tests/integration/test_lists/waives.txt
@@ -430,11 +430,11 @@ accuracy/test_cli_flow.py::TestLlama3_2_1B::test_cyclic_kv_cache SKIP (https://n
 accuracy/test_cli_flow.py::TestSantacoder::test_auto_dtype SKIP (https://nvbugs/5231468)
 accuracy/test_cli_flow.py::TestLlama3_2_1B::test_cyclic_kv_cache SKIP (https://nvbugs/5231310)
 test_e2e.py::test_ptp_quickstart_multimodal[NVILA-8B-FP16-vila/NVILA-8B-image] SKIP (https://nvbugs/5233423)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5239087)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5239087)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5239087)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5239087)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5234002)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[tp4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5239087)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus[ep4-mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5239087)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[tp4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5239087)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales_4gpus[ep4-mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5239087)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5234002)
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[-] SKIP (https://nvbugs/5234002)
 examples/test_gemma.py::test_llm_hf_gemma_quantization_1gpu[gemma-2-27b-it-fp8-bfloat16-8] SKIP (https://nvbugs/5234164)
 full::GH200/examples/test_commandr.py::test_llm_commandr_v01_single_gpu_summary[disable_weight_only] SKIP (https://nvbugs/5250460)
@@ -472,20 +472,20 @@ triton_server/test_triton.py::test_qwen2_vl[qwen2_vl] SKIP
 triton_server/test_triton.py::test_gpt_ib_speculative_decoding_bls[gpt-ib-speculative-decoding-bls] SKIP
 triton_server/test_triton_llm.py::test_mistral_v1_multi_models[False-1-False-True-False-0-128-enableDecoupleMode-inflight_fused_batching-disableTrtOverlap-max_utilization-4096-1-1-1-False-ensemble] SKIP
 accuracy/test_cli_flow.py::TestTinyLlama1_1BChat::test_pp4 SKIP (https://nvbugs/5287097)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5286795)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True] SKIP (https://nvbugs/5285965)
-accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5286795)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=0-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5285965)
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5285965)
 accuracy/test_llm_api_pytorch.py::TestDeepSeekR1::test_fp8_blockscale[latency] SKIP (https://nvbugs/5285965)