diff --git a/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/README.md b/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/README.md
index cce5a097f..b43e87fdf 100644
--- a/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/README.md
+++ b/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/README.md
@@ -9,7 +9,7 @@ pip install vsa
 
 ### 1. Download dataset:
 ```bash
-bash examples/distill/Wan-Syn-480P/download_dataset.sh
+bash examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/download_dataset.sh
 ```
 
 ### 2. Configure and run distillation:
diff --git a/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/distill_dmd_t2v_1.3B.sh b/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/distill_dmd_t2v_1.3B.sh
new file mode 100644
index 000000000..9ca03ab26
--- /dev/null
+++ b/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/distill_dmd_t2v_1.3B.sh
@@ -0,0 +1,119 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+############################################
+# Single node, 6 GPUs
+############################################
+NUM_GPUS=6
+export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5
+
+
+export WANDB_MODE="online"
+export WANDB_BASE_URL="https://api.wandb.ai"
+export TOKENIZERS_PARALLELISM=false
+export FASTVIDEO_ATTENTION_BACKEND=FLASH_ATTN   # or TORCH_SDPA
+export NCCL_P2P_DISABLE=1
+export TORCH_NCCL_ENABLE_MONITORING=0
+export TRITON_CACHE_DIR=/tmp/triton_cache
+
+echo "NUM_GPUS:    $NUM_GPUS"
+echo "CUDA_VISIBLE_DEVICES: $CUDA_VISIBLE_DEVICES"
+
+############################################
+# Configs
+############################################
+MODEL_PATH="Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
+DATA_DIR=data/Wan-Syn_77x448x832_600k/train
+VALIDATION_DATASET_FILE=data/Wan-Syn_77x448x832_600k/validation_6.json
+OUTPUT_DIR="checkpoints/wan_t2v_finetune"
+
+# Training arguments
+training_args=(
+  --tracker_project_name wan_t2v_distill_dmd
+  --output_dir "$OUTPUT_DIR"
+  --max_train_steps 4000
+  --train_batch_size 1
+  --train_sp_batch_size 1
+  --gradient_accumulation_steps 1
+  --num_latent_t 21
+  --num_height 480
+  --num_width 832
+  --num_frames 81
+  --enable_gradient_checkpointing_type "full"
+)
+
+# Parallel arguments (adjusted to 6 GPUs)
+parallel_args=(
+  --num_gpus 6
+  --sp_size 1
+  --tp_size 1
+  --hsdp_replicate_dim 1
+  --hsdp_shard_dim 6
+)
+
+# Model arguments
+model_args=(
+  --model_path "$MODEL_PATH"
+  --pretrained_model_name_or_path "$MODEL_PATH"
+)
+
+# Dataset arguments
+dataset_args=(
+  --data_path "$DATA_DIR"
+  --dataloader_num_workers 4
+)
+
+# Validation arguments
+validation_args=(
+  --log_validation
+  --validation_dataset_file "$VALIDATION_DATASET_FILE"
+  --validation_steps 100
+  --validation_sampling_steps "3"
+  --validation_guidance_scale "6.0"
+)
+
+# Optimizer arguments
+optimizer_args=(
+  --learning_rate 2e-6
+  --mixed_precision "bf16"
+  --training_state_checkpointing_steps 500
+  --weight_only_checkpointing_steps 500
+  --weight_decay 0.01
+  --max_grad_norm 1.0
+)
+
+# Miscellaneous arguments
+miscellaneous_args=(
+  --inference_mode False
+  --checkpoints_total_limit 3
+  --training_cfg_rate 0.0
+  --dit_precision "fp32"
+  --ema_start_step 0
+  --flow_shift 8
+  --seed 1000
+)
+
+# DMD arguments
+dmd_args=(
+  --dmd_denoising_steps '1000,757,522'
+  --min_timestep_ratio 0.02
+  --max_timestep_ratio 0.98
+  --generator_update_interval 5
+  --real_score_guidance_scale 3.5
+)
+
+############################################
+# Launch (no rendezvous flags needed)
+############################################
+set -x
+torchrun \
+  --nproc_per_node="$NUM_GPUS" \
+  fastvideo/training/wan_distillation_pipeline.py \
+    "${parallel_args[@]}" \
+    "${model_args[@]}" \
+    "${dataset_args[@]}" \
+    "${training_args[@]}" \
+    "${optimizer_args[@]}" \
+    "${validation_args[@]}" \
+    "${miscellaneous_args[@]}" \
+    "${dmd_args[@]}"