diff --git a/eval/sample.sh b/eval/sample.sh
index 1c52506..eff1368 100644
--- a/eval/sample.sh
+++ b/eval/sample.sh
@@ -260,10 +260,17 @@ function run_vbench() {
           --resolution $VBENCH_RES --aspect-ratio $VBENCH_ASP_RATIO --num-sampling-steps ${NUM_SAMPLING_STEPS} --flow ${FLOW} \
           --batch-size $VBENCH_BS --num-frames $NUM_FRAMES --start-index $1 --end-index $2
         else
-          eval $CMD --ckpt-path $CKPT --save-dir ${OUTPUT}_vbench --prompt-as-path --num-sample 5 \
-          --prompt-path assets/texts/VBench/all_dimension.txt \
-          --resolution $VBENCH_RES --aspect-ratio $VBENCH_ASP_RATIO --num-sampling-steps ${NUM_SAMPLING_STEPS} --flow ${FLOW} --llm-refine ${LLM_REFINE} \
-          --batch-size $VBENCH_BS --num-frames $NUM_FRAMES --start-index $1 --end-index $2
+          if [ "${FLOW}" = "None" ]; then
+            eval $CMD --ckpt-path $CKPT --save-dir ${OUTPUT}_vbench --prompt-as-path --num-sample 5 \
+            --prompt-path assets/texts/VBench/all_dimension.txt \
+            --resolution $VBENCH_RES --aspect-ratio $VBENCH_ASP_RATIO --num-sampling-steps ${NUM_SAMPLING_STEPS} --llm-refine ${LLM_REFINE} \
+            --batch-size $VBENCH_BS --num-frames $NUM_FRAMES --start-index $1 --end-index $2
+          else
+            eval $CMD --ckpt-path $CKPT --save-dir ${OUTPUT}_vbench --prompt-as-path --num-sample 5 \
+            --prompt-path assets/texts/VBench/all_dimension.txt \
+            --resolution $VBENCH_RES --aspect-ratio $VBENCH_ASP_RATIO --num-sampling-steps ${NUM_SAMPLING_STEPS} --flow ${FLOW} --llm-refine ${LLM_REFINE} \
+            --batch-size $VBENCH_BS --num-frames $NUM_FRAMES --start-index $1 --end-index $2
+          fi
         fi
       fi
     fi
diff --git a/eval/vbench/calc_vbench.py b/eval/vbench/calc_vbench.py
index b2505bf..e5570a1 100644
--- a/eval/vbench/calc_vbench.py
+++ b/eval/vbench/calc_vbench.py
@@ -1,37 +1,46 @@
 import argparse
 import os
-from vbench import VBench
-import torch
 import time
 
+import torch
+
+from vbench import VBench
+
 full_info_path = "eval/vbench/VBench_full_info.json"
 dimensions = [
-    # Quality Score
-    "subject_consistency",
-    "background_consistency",
-    "motion_smoothness",
-    "dynamic_degree",
-    "aesthetic_quality",
-    "imaging_quality",
-    "temporal_flickering",
-    # Semantic Score
-    "object_class",
-    "multiple_objects",
-    "color",
-    "spatial_relationship",
-    "scene",
-    "temporal_style",
-    "overall_consistency",
-    "human_action",
-    "appearance_style",
+    # a: 10min
+    "subject_consistency",  # 4min
+    "imaging_quality",  # 6min
+    # b: 12min
+    "background_consistency",  # 2min
+    "motion_smoothness",  # 5min
+    "overall_consistency",  # 2min
+    "human_action",  # 3min
+    # c: 14min
+    "multiple_objects",  # 14min
+    # d: 14min
+    "spatial_relationship",  # 14min
+    # e: 12min
+    "object_class",  # 12min
+    # f: 12min
+    "color",  # 12min
+    # g: 10.5min
+    "aesthetic_quality",  # 2.5min
+    "appearance_style",  # 6min
+    "temporal_flickering",  # 2min
+    # h: 9min
+    "scene",  # 3min
+    "temporal_style",  # 2min
+    "dynamic_degree",  # 4min
 ]
 
+
 def parse_args():
     parser = argparse.ArgumentParser()
     parser.add_argument("video_folder", type=str)  # samples/samples..._vbench/eval
     parser.add_argument("model_ckpt", type=str)
-    parser.add_argument("--start", type=int, default=0) # start index of dimension to be evaluated
-    parser.add_argument("--end", type=int, default=-1) # start index of dimension to be evaluated
+    parser.add_argument("--start", type=int, default=0)  # start index of dimension to be evaluated
+    parser.add_argument("--end", type=int, default=-1)  # start index of dimension to be evaluated
 
     args = parser.parse_args()
     return args
@@ -44,23 +53,23 @@ if __name__ == "__main__":
     video_path = args.video_folder
 
     kwargs = {}
-    kwargs['imaging_quality_preprocessing_mode'] = 'longer' # use VBench/evaluate.py default
+    kwargs["imaging_quality_preprocessing_mode"] = "longer"  # use VBench/evaluate.py default
 
     start_time = time.time()
 
     # NOTE: important to use torch.device("cuda"), else will have issue with object_class third_party module
     my_VBench = VBench(torch.device("cuda"), full_info_path, output_dir)
-    if args.end == -1: # adjust end accordingly
+    if args.end == -1:  # adjust end accordingly
         args.end = len(dimensions)
-    for dim in dimensions[args.start:args.end]:
+    for dim in dimensions[args.start : args.end]:
         my_VBench.evaluate(
             videos_path=video_path,
             name=dim,
             local=False,
             read_frame=False,
             dimension_list=[dim],
-            mode='vbench_standard',
-            **kwargs
+            mode="vbench_standard",
+            **kwargs,
         )
 
-    print("Runtime: %s seconds " % (time.time() - start_time))
\ No newline at end of file
+    print("Runtime: %s seconds " % (time.time() - start_time))
diff --git a/eval/vbench/launch_calc.sh b/eval/vbench/launch_calc.sh
index 53114b9..9f14ce5 100644
--- a/eval/vbench/launch_calc.sh
+++ b/eval/vbench/launch_calc.sh
@@ -7,11 +7,10 @@ mkdir -p $LOG_BASE
 echo "Logging to $LOG_BASE"
 
 GPUS=(0 1 2 3 4 5 6 7)
-START_INDEX_LIST=(0 2 4 6 8 10 12 14)
-END_INDEX_LIST=(2 4 6 8 10 12 14 16)
+START_INDEX_LIST=(0 2 6 7 8 9 10 13)
+END_INDEX_LIST=(2 6 7 8 9 10 13 16)
 TASK_ID_LIST=(calc_vbench_a calc_vbench_b calc_vbench_c calc_vbench_d calc_vbench_e calc_vbench_f calc_vbench_g calc_vbench_h) # for log records only
 
-
 for i in "${!GPUS[@]}"; do
     CUDA_VISIBLE_DEVICES=${GPUS[i]} python eval/vbench/calc_vbench.py $VIDEO_DIR $CKPT_DIR --start ${START_INDEX_LIST[i]} --end ${END_INDEX_LIST[i]} > ${LOG_BASE}/${TASK_ID_LIST[i]}.log 2>&1 &
 done