diff --git a/.github/run-benchmark-as-lit-jobs.py b/.github/run-benchmark-as-lit-jobs.py
index 5b9de62bd1..f5e89405e1 100644
--- a/.github/run-benchmark-as-lit-jobs.py
+++ b/.github/run-benchmark-as-lit-jobs.py
@@ -16,7 +16,7 @@ def main(gh_run_id: str = ""):
     print("Uploading package and benchmark script...")
     s.upload_folder("dist", remote_path="dist")
     pkg_path = glob.glob("dist/*.whl")[0]
-    s.upload_file("examples/coverage/requirements.txt", remote_path="benchmarks/requirements.txt")
+    s.upload_file("examples/quickstart/benchmarks/requirements.txt", remote_path="benchmarks/requirements.txt")
     s.upload_file("thunder/benchmarks/benchmark_hf.py", remote_path="benchmarks/benchmark_hf.py")
 
     print("Starting studio...")
diff --git a/examples/quickstart/benchmarks/requirements.txt b/examples/quickstart/benchmarks/requirements.txt
new file mode 100644
index 0000000000..5f16f94900
--- /dev/null
+++ b/examples/quickstart/benchmarks/requirements.txt
@@ -0,0 +1,5 @@
+transformers==4.52.4
+numpy<2.0
+torch==2.7.1
+nvfuser-cu128-torch27
+nvidia-cudnn-frontend
diff --git a/thunder/benchmarks/benchmark_hf.py b/thunder/benchmarks/benchmark_hf.py
index 68bd56dc81..a84391b956 100644
--- a/thunder/benchmarks/benchmark_hf.py
+++ b/thunder/benchmarks/benchmark_hf.py
@@ -5,17 +5,10 @@
 
 import thunder
 from thunder.dev_utils.benchmark import benchmark_n
-from thunder.recipes.base import BaseRecipe
+from thunder.recipes.hf_transformers import HFTransformers
 
 from torch.profiler import profile, record_function, ProfilerActivity
 
-
-class DebugRecipe(BaseRecipe):
-    def setup_config(self):
-        config = super().setup_config()
-        return config
-
-
 device = "cuda"
 model_name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
 
@@ -28,8 +21,8 @@ def setup_config(self):
 plugins_str = "" if plugins is None else plugins if isinstance(plugins, str) else "-".join(plugins)
 
 # Define recipes
-nvfuser_recipe = DebugRecipe()
-torchcompile_recipe = DebugRecipe(fuser="torch.compile")
+nvfuser_recipe = HFTransformers()
+torchcompile_recipe = HFTransformers(fuser="torch.compile")
 recipes = [nvfuser_recipe, torchcompile_recipe]
 
 
@@ -68,6 +61,8 @@ def run_and_profile(tag: str, fn, model, inp, compiled_models: dict[str, torch.n
             with open(profile_path, "w") as f:
                 f.write(thunder_prof.key_averages().table(sort_by="cpu_time_total"))
 
+        print(timings)
+
     with open(root / f"{tag}_timings_{plugins_str}.txt", "w") as f:
         f.write("\n".join(timings))
 
diff --git a/thunder/recipes/hf_transformers.py b/thunder/recipes/hf_transformers.py
index 0dd3f1bc31..2440beaa41 100644
--- a/thunder/recipes/hf_transformers.py
+++ b/thunder/recipes/hf_transformers.py
@@ -181,6 +181,7 @@ class HFTransformers(BaseRecipe):
 
     Args:
         show_progress (bool, optional): Forwarded to :class:`BaseRecipe`.
+        fuser (str, optional): which fuser to use, default NvFuser.
         interpreter (str, optional): Thunder interpreter to use.
         plugins (Iterable | None, optional): Extra Thunder plugins.
     """
@@ -188,10 +189,11 @@ class HFTransformers(BaseRecipe):
     def __init__(
         self,
         show_progress=False,
+        fuser="nvfuser",
         interpreter="thunder.jit",
         plugins=None,
     ):
-        super().__init__(show_progress=show_progress, interpreter=interpreter, plugins=plugins)
+        super().__init__(show_progress=show_progress, fuser=fuser, interpreter=interpreter, plugins=plugins)
 
         # for kv-cache inplace ops
         self.inplace_index_copy_transform = InplaceIndexCopyTransform()