diff --git a/vall_e/models/ar_nar.py b/vall_e/models/ar_nar.py
index fd27e99..d8ed04e 100644
--- a/vall_e/models/ar_nar.py
+++ b/vall_e/models/ar_nar.py
@@ -486,7 +486,7 @@ class AR_NAR(Base):
 				null_inputs = super().inputs(
 					text_list=null_text,
 					proms_list=null_prom,
-					resps_list=resps_list,
+					resps_list=prev_list,
 					lang_list=lang_list,
 					tone_list=tone_list,
 					quant_levels=quant_levels,
@@ -496,7 +496,8 @@ class AR_NAR(Base):
 					quant_levels=quant_levels,
 					#layer_skip_variables=sampling_layer_skip_variables,
 				)
-				for seq_len, logit, null_logit in zip(len_list, output.logits, null_output.logits):
+				for resp, logit, null_logit in zip(resps_list, output.logits, null_output.logits):
+					seq_len = resp.shape[0]
 					logit[-seq_len:] = null_logit[-seq_len:] + ( logit[-seq_len:] - null_logit[-seq_len:] ) * cfg_strength
 
 			sampled = super().sample(
@@ -655,6 +656,7 @@ class AR_NAR(Base):
 			# it would technically be faster to just append the new token's embedding to the inputs, but there's a VERY small performance gain from doing it, so it's not worth it
 			text_list = [ sequence_list[i] if task in text_task else text_list[i] for i, task in enumerate(task_list) ]
 			resps_list = [ sequence_list[i] if task not in text_task else resps_list[i] for i, task in enumerate(task_list) ]
+			quant_levels = [ 0 for _ in range( max( batch_size, beam_width ) ) ]
 
 			inputs = self.inputs(
 				text_list=text_list,
@@ -664,7 +666,7 @@ class AR_NAR(Base):
 				tone_list=tone_list,
 				len_list=len_list,
 				task_list=task_list,
-				quant_levels=[ 0 for _ in range( max( batch_size, beam_width ) ) ]
+				quant_levels=quant_levels,
 			)
 
 			# to-do: find an elegant way to write this
@@ -689,7 +691,8 @@ class AR_NAR(Base):
 					quant_levels=quant_levels,
 					#layer_skip_variables=sampling_layer_skip_variables,
 				)
-				for seq_len, logit, null_logit in zip(len_list, output.logits, null_output.logits):
+				for resp, logit, null_logit in zip(resps_list, output.logits, null_output.logits):
+					seq_len = resp.shape[0] + 1
 					logit[-seq_len:] = null_logit[-seq_len:] + ( logit[-seq_len:] - null_logit[-seq_len:] ) * cfg_strength
 			
 			logits, state = output.logits, output.state
diff --git a/vall_e/webui.py b/vall_e/webui.py
index f80ca5e..4c2b2db 100644
--- a/vall_e/webui.py
+++ b/vall_e/webui.py
@@ -233,6 +233,7 @@ def do_inference_tts( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 	parser.add_argument("--layer-skip-varentropy-threshold", type=int, default=kwargs["layer-skip-varentropy-threshold"])
 	parser.add_argument("--refine-on-stop", action="store_true")
 	parser.add_argument("--denoise-start", type=float, default=0.0)
+	parser.add_argument("--cfg-strength", type=float, default=kwargs['cfg-strength'])
 	args, unknown = parser.parse_known_args()
 
 	if is_windows:
@@ -280,6 +281,7 @@ def do_inference_tts( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 		prefix_silence=args.prefix_silence,
 		input_prompt_prefix=args.input_prompt_prefix,
 		input_prompt_length=args.input_prompt_length,
+		cfg_strength=args.cfg_strength,
 	)
 	
 	with timer("Inferenced in", callback=lambda msg: gr.Info( msg )) as t: