diff --git a/tortoise/do_tts.py b/tortoise/do_tts.py
index 77df67d..b74466c 100644
--- a/tortoise/do_tts.py
+++ b/tortoise/do_tts.py
@@ -18,6 +18,7 @@ if __name__ == '__main__':
     parser.add_argument('--output_path', type=str, help='Where to store outputs.', default='results/')
     parser.add_argument('--model_dir', type=str, help='Where to find pretrained model checkpoints. Tortoise automatically downloads these to .models, so this'
                                                       'should only be specified if you have custom checkpoints.', default='.models')
+    parser.add_argument('--candidates', type=int, help='How many output candidates to produce per-voice.', default=3)
     args = parser.parse_args()
     os.makedirs(args.output_path, exist_ok=True)
 
@@ -26,7 +27,11 @@ if __name__ == '__main__':
     selected_voices = args.voice.split(',')
     for k, voice in enumerate(selected_voices):
         voice_samples, conditioning_latents = load_voice(voice)
-        gen = tts.tts_with_preset(args.text, voice_samples=voice_samples, conditioning_latents=conditioning_latents,
+        gen = tts.tts_with_preset(args.text, k=args.candidates, voice_samples=voice_samples, conditioning_latents=conditioning_latents,
                                   preset=args.preset, clvp_cvvp_slider=args.voice_diversity_intelligibility_slider)
-        torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}.wav'), gen.squeeze(0).cpu(), 24000)
+        if isinstance(gen, list):
+            for j, g in enumerate(gen):
+                torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}_{j}.wav'), g.squeeze(0).cpu(), 24000)
+        else:
+            torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}.wav'), gen.squeeze(0).cpu(), 24000)