diff --git a/src/h3_blackwell_runtime/packing.py b/src/h3_blackwell_runtime/packing.py
index 802664c..4cd5596 100644
--- a/src/h3_blackwell_runtime/packing.py
+++ b/src/h3_blackwell_runtime/packing.py
@@ -70,7 +70,7 @@ class H3PromptPacker:
         text: torch.Tensor,
         video: torch.Tensor,
         audio: torch.Tensor,
-        sigma: float,
+        sigma: float | torch.Tensor,
         model_timesteps: torch.Tensor | None = None,
     ) -> tuple[torch.Tensor, torch.Tensor, list[tuple[int, int, int]], tuple[int, int, int], tuple[int, int, int]]:
         if text.shape[-1] == 5120:
@@ -84,7 +84,7 @@ class H3PromptPacker:
         text_length, audio_length = text_rows.shape[0], audio_rows.shape[0]
         hidden = torch.cat((text_rows, audio_rows, video_rows))
         if model_timesteps is None:
-            video_sigma = torch.tensor(float(sigma), device=hidden.device).clamp(min=1e-6)
+            video_sigma = torch.as_tensor(sigma, device=hidden.device, dtype=torch.float32).clamp(min=1e-6)
             base = video_sigma / (12.0 + video_sigma * (1.0 - 12.0))
             audio_sigma = 3.0 * base / (1.0 + (3.0 - 1.0) * base)
             video_time, audio_time = (1.0 - video_sigma).item(), (1.0 - audio_sigma).item()
diff --git a/src/h3_blackwell_runtime/sampler.py b/src/h3_blackwell_runtime/sampler.py
index d07ff10..3962745 100644
--- a/src/h3_blackwell_runtime/sampler.py
+++ b/src/h3_blackwell_runtime/sampler.py
@@ -47,6 +47,11 @@ def _audio_sigma(video_sigma: torch.Tensor) -> torch.Tensor:
     return 3.0 * base / (1.0 + (3.0 - 1.0) * base)
 
 
+def _model_sigma(video_sigma: torch.Tensor) -> torch.Tensor:
+    """Comfy BaseModel's flow timestep round-trip seen by the H3 diffusion model."""
+    return (video_sigma * 1000.0).float() / 1000.0
+
+
 @torch.inference_mode()
 def sample_video_res_multistep(
     model,
@@ -73,7 +78,7 @@ def sample_video_res_multistep(
         carry = sigma_audio / sigma
         native_audio = audio_carried.to(torch.bfloat16) * carry
         step_timesteps = None if model_timesteps is None else model_timesteps[previous_index]
-        hidden, times, segments, positions, video_segment, audio_segment = packer(text, video, native_audio, float(sigma), step_timesteps)
+        hidden, times, segments, positions, video_segment, audio_segment = packer(text, video, native_audio, _model_sigma(sigma), step_timesteps)
         raw_video, raw_audio = model(hidden, times, positions, segments, video_segment, audio_segment)
         raw_video = raw_video.to(torch.bfloat16).float()
         raw_audio = raw_audio.to(torch.bfloat16)
@@ -105,7 +110,7 @@ def sample_video_euler(model, packer: H3PromptPacker, text: torch.Tensor, video:
     sigmas = beta_sigmas(steps, device=video.device)
     for index in range(steps):
         sigma = sigmas[index]
-        hidden, timesteps, segments, positions, video_segment, audio_segment = packer(text, video, audio, float(sigma))
+        hidden, timesteps, segments, positions, video_segment, audio_segment = packer(text, video, audio, _model_sigma(sigma))
         velocity, _ = model(hidden, timesteps, positions, segments, video_segment, audio_segment)
         velocity = unpatchify_video(velocity, video.shape[2], video.shape[-2], video.shape[-1])
         video.add_(velocity.to(video.dtype), alpha=float(sigmas[index + 1] - sigma))