diff --git a/tests/multimodal/test_video.py b/tests/multimodal/test_video.py
index f07a6d888e..1a7b63ae92 100644
--- a/tests/multimodal/test_video.py
+++ b/tests/multimodal/test_video.py
@@ -14,6 +14,7 @@ from transformers import AutoVideoProcessor
 from transformers.video_utils import VideoMetadata
 
 from vllm.assets.base import get_vllm_public_assets
+from vllm.models.minimax_m3.common.mm_preprocess import MiniMaxM3VideoBackend
 from vllm.multimodal.video import (
     PYNVVIDEOCODEC_DECODER_CACHE_SIZE,
     PYNVVIDEOCODEC_VIDEO_BACKEND,
@@ -388,6 +389,12 @@ def test_cosmos3_edge_uses_qwen3_vl_video_backend():
             {"fps": 2},
             id="qwen2_5_vl",
         ),
+        pytest.param(
+            "MiniMaxAI/MiniMax-M3",
+            MiniMaxM3VideoBackend,
+            None,
+            id="minimax_m3_vl",
+        ),
     ],
 )
 def test_video_processor_from_model_repo(
diff --git a/vllm/models/minimax_m3/common/mm_preprocess.py b/vllm/models/minimax_m3/common/mm_preprocess.py
index 208adfffea..8ec8b8191a 100644
--- a/vllm/models/minimax_m3/common/mm_preprocess.py
+++ b/vllm/models/minimax_m3/common/mm_preprocess.py
@@ -3,8 +3,9 @@
 
 import math
 from collections.abc import Mapping, Sequence
-from typing import cast
+from typing import Any, Literal, cast
 
+import numpy.typing as npt
 import torch
 from transformers import BatchFeature
 from transformers.video_utils import VideoMetadata
@@ -469,10 +470,39 @@ class MiniMaxM3VLMultiModalProcessor(
         ]
 
 
-# TODO(Isotr0py): Tie with MinimaxVideoProcessor
-# after https://github.com/vllm-project/vllm/pull/44126
-@VIDEO_LOADER_REGISTRY.register("minimax_m3_vl")
+@VIDEO_LOADER_REGISTRY.register(
+    name="minimax_m3_vl",
+    video_processor="MiniMaxM3VLVideoProcessor",
+)
 class MiniMaxM3VideoBackend(VideoBackend):
+    @classmethod
+    def load_bytes(
+        cls,
+        data: bytes,
+        num_frames: int = -1,
+        fps: int = 1,
+        max_duration: int = 300,
+        frame_recovery: bool = False,
+        *,
+        backend: Literal[
+            "opencv",
+            "pyav",
+            "torchcodec",
+            "pynvvideocodec",
+            "deepstream",
+        ] = "opencv",
+        **kwargs,
+    ) -> tuple[npt.NDArray, dict[str, Any]]:
+        return super().load_bytes(
+            data,
+            num_frames=num_frames,
+            fps=fps,
+            max_duration=max_duration,
+            frame_recovery=frame_recovery,
+            backend=backend,
+            **kwargs,
+        )
+
     @classmethod
     def compute_frames_index_to_sample(
         cls,
@@ -483,7 +513,6 @@ class MiniMaxM3VideoBackend(VideoBackend):
         total_frames = source.total_frames_num
         video_fps = source.original_fps
         fps = target.fps
-
         if total_frames <= 0 or video_fps <= 0 or fps <= 0:
             return [0] if total_frames > 0 else []
 
@@ -503,8 +532,9 @@ class MiniMaxM3VideoBackend(VideoBackend):
                 break
             indices.append(target_frame)
             prev_kept_ts = target_frame / video_fps
-
-        last_frame_idx = total_frames - 1
+        # Because HF sample_frames includes the last frame,
+        # we will use HF as the standard.
+        last_frame_idx = total_frames
         last_ts = last_frame_idx / video_fps
         if indices and indices[-1] != last_frame_idx and last_ts - prev_kept_ts > eps:
             indices.append(last_frame_idx)