diff --git a/userbenchmark/dynamo/dynamobench/common.py b/userbenchmark/dynamo/dynamobench/common.py
index c1d11c596..ed724c69d 100644
--- a/userbenchmark/dynamo/dynamobench/common.py
+++ b/userbenchmark/dynamo/dynamobench/common.py
@@ -146,6 +146,12 @@ class CI(NamedTuple):
 except ImportError:
     INTERNAL_CI_SKIP_DYNAMIC_BATCH_ONLY = set()
 
+try:
+    from pytorch.benchmark.fb.run_utils import trace_handler
+except ImportError:
+    trace_handler = lambda *args: None
+
+
 CI_SKIP_DYNAMIC_BATCH_ONLY = {
     "sam",
     # See https://github.com/mindee/doctr/blob/f2114758d529ed8d3d0030581638f0520b6b98d8/doctr/models/detection/core.py#L89
@@ -910,7 +916,7 @@ def maybe_mark_profile(*args, **kwargs):
 
     times = args.iterations_per_run
 
-    with maybe_profile(args.export_profiler_trace) as p:
+    with maybe_profile(args.export_profiler_trace, **args.profile_details) as p:
         for rep in trange(args.repeat, desc="running benchmark"):
             inputs = (
                 randomize_input(copy.deepcopy(example_inputs))
@@ -1065,7 +1071,7 @@ def maybe_mark_profile(*args, **kwargs):
     tolerance = args.xla_tolerance if args.trace_on_xla else 1e-4
     torch._dynamo.config.repro_tolerance = tolerance
 
-    with maybe_profile(args.export_profiler_trace) as p:
+    with maybe_profile(args.export_profiler_trace, **args.profile_details) as p:
         if args.export_aot_inductor:
             frozen_model_iter_fn = export_aot_inductor(model, example_inputs)
         else:
@@ -1114,9 +1120,13 @@ def maybe_mark_profile(*args, **kwargs):
         name = args.profiler_trace_name + "_" + model.name
         if hasattr(args, "rank"):
             name += f"_rank_{args.rank}"
-        name += ".json"
-        name = os.path.join(torch._dynamo.config.base_dir, name)
-        p.export_chrome_trace(name)
+        if args.export_perfdoctor:
+            trace_handler(name, p)
+        else:
+            name += ".json"
+            name = os.path.join(torch._dynamo.config.base_dir, name)
+            p.export_chrome_trace(name)
+
     median = np.median(timings, axis=0)
     speedup = median[0] / median[1]
     if args.dump_raw_metrics:
@@ -3918,6 +3928,16 @@ def get_example_inputs(self):
         "--profiler_trace_name",
         help="Overwrites exported trace name",
     )
+    parser.add_argument(
+        "--profile-details",
+        action="store_true",
+        help="More detailed profiler trace."
+    )
+    parser.add_argument(
+        "--export-perfdoctor",
+        action="store_true",
+        help="Export Chrome trace to perf doctor. (internal only)",
+    )
     parser.add_argument(
         "--diff-branch",
         default=diff_branch_default,
@@ -4755,6 +4775,15 @@ def model_iter_fn_and_mark_step(*args, **kwargs):
         return
 
     if args.export_profiler_trace:
+        if args.profile_details:
+            args.profile_details = {
+                "record_shapes": True,
+                "profile_memory": True,
+                "with_stack": True,
+                "with_modules": True,
+            }
+        else:
+            args.profile_details = {}
         if args.profiler_trace_name is None:
             if args.backend:
                 args.profiler_trace_name = args.backend