diff --git a/tritonbench/components/ncu/nsys_analyzer.py b/tritonbench/components/ncu/nsys_analyzer.py
index dc4364e1..2f50c111 100644
--- a/tritonbench/components/ncu/nsys_analyzer.py
+++ b/tritonbench/components/ncu/nsys_analyzer.py
@@ -80,7 +80,9 @@ def read_nsys_report(
 
     # Define mapping of metrics to their values. The keys must be in nsys_bench_metrics.
     metrics_map = {
-        "nsys_kernel_durations": kernel_duration,
+        # Because tritonbench takes the median of numerical values, we need to convert
+        # the list of floats to a list of strings.
+        "nsys_kernel_durations": [str(duration) for duration in kernel_duration],
         "nsys_kernel_names": kernel_names,
         "nsys_gpu_kernel_sum": sum_kernel_duration,
         "nsys_nvtx_range_duration": nvtx_range_duration,
diff --git a/tritonbench/utils/triton_op.py b/tritonbench/utils/triton_op.py
index 2184cda0..a03048a5 100644
--- a/tritonbench/utils/triton_op.py
+++ b/tritonbench/utils/triton_op.py
@@ -67,7 +67,12 @@ class BenchmarkOperatorBackend:
 REGISTERED_METRICS: Dict[str, List[str]] = {}
 REGISTERED_X_VALS: Dict[str, str] = {}
 BASELINE_BENCHMARKS: Dict[str, str] = {}
-BASELINE_SKIP_METRICS = {"speedup", "accuracy", "mem_footprint_compression_ratio"}
+BASELINE_SKIP_METRICS = {
+    "speedup",
+    "accuracy",
+    "mem_footprint_compression_ratio",
+    "nsys_gpu_speedup",
+}
 X_ONLY_METRICS = set(["hw_roofline"])
 PRECISION_DTYPE_MAPPING = {
     "fp32": torch.float32,
@@ -1094,7 +1099,17 @@ def _init_extra_metrics() -> Dict[str, Any]:
                     )
                     for metric_name, metric_value in nsys_analyzer_results.items():
                         metrics.extra_metrics[metric_name] = metric_value
-
+            if "nsys_gpu_speedup" in self.required_metrics:
+                metrics.nsys_gpu_speedup = (
+                    self.baseline_metrics.nsys_gpu_kernel_sum
+                    / metrics.nsys_gpu_kernel_sum
+                    if (
+                        self.baseline_metrics
+                        and self.baseline_metrics.nsys_gpu_kernel_sum
+                    )
+                    and metrics.nsys_gpu_kernel_sum
+                    else None
+                )
             if "kineto_trace" in self.required_metrics:
                 metrics.kineto_trace = self.kineto_trace(input_id, fn)
             if "best_config" in self.required_metrics: