diff --git a/src/diffusers/pipelines/ltx2/pipeline_ltx2_image2video.py b/src/diffusers/pipelines/ltx2/pipeline_ltx2_image2video.py
index b1711e2831..a33462f70c 100644
--- a/src/diffusers/pipelines/ltx2/pipeline_ltx2_image2video.py
+++ b/src/diffusers/pipelines/ltx2/pipeline_ltx2_image2video.py
@@ -811,6 +811,7 @@ class LTX2ImageToVideoPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVideoL
         num_frames: int = 121,
         frame_rate: float = 24.0,
         num_inference_steps: int = 40,
+        sigmas: Optional[List[float]] = None,
         timesteps: List[int] = None,
         guidance_scale: float = 4.0,
         guidance_rescale: float = 0.0,
@@ -851,6 +852,10 @@ class LTX2ImageToVideoPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVideoL
             num_inference_steps (`int`, *optional*, defaults to 40):
                 The number of denoising steps. More denoising steps usually lead to a higher quality image at the
                 expense of slower inference.
+            sigmas (`List[float]`, *optional*):
+                Custom sigmas to use for the denoising process with schedulers which support a `sigmas` argument in
+                their `set_timesteps` method. If not defined, the default behavior when `num_inference_steps` is passed
+                will be used.
             timesteps (`List[int]`, *optional*):
                 Custom timesteps to use for the denoising process with schedulers which support a `timesteps` argument
                 in their `set_timesteps` method. If not defined, the default behavior when `num_inference_steps` is
@@ -1028,7 +1033,7 @@ class LTX2ImageToVideoPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVideoL
         latent_width = width // self.vae_spatial_compression_ratio
         video_sequence_length = latent_num_frames * latent_height * latent_width
 
-        sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps)
+        sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps) if sigmas is None else sigmas
         mu = calculate_shift(
             video_sequence_length,
             self.scheduler.config.get("base_image_seq_len", 1024),