diff --git a/src/transformers/models/musicgen/modeling_musicgen.py b/src/transformers/models/musicgen/modeling_musicgen.py
index 11a0c4083cb7..49278ec03691 100644
--- a/src/transformers/models/musicgen/modeling_musicgen.py
+++ b/src/transformers/models/musicgen/modeling_musicgen.py
@@ -27,7 +27,7 @@
 
 from ...activations import ACT2FN
 from ...generation.configuration_utils import GenerationConfig
-from ...generation.logits_process import LogitsProcessorList
+from ...generation.logits_process import ClassifierFreeGuidanceLogitsProcessor, LogitsProcessorList
 from ...generation.stopping_criteria import StoppingCriteriaList
 from ...modeling_outputs import (
     BaseModelOutput,
@@ -1354,7 +1354,12 @@ def generate(
             and generation_config.do_sample is True
         )
 
-        # 8. prepare distribution pre_processing samplers
+        # 8. prepare batched CFG externally (to enable coexistance with the unbatched CFG)
+        if generation_config.guidance_scale is not None and generation_config.guidance_scale > 1:
+            logits_processor.append(ClassifierFreeGuidanceLogitsProcessor(generation_config.guidance_scale))
+            generation_config.guidance_scale = None
+
+        # 9. prepare distribution pre_processing samplers
         logits_processor = self._get_logits_processor(
             generation_config=generation_config,
             input_ids_seq_length=input_ids_seq_length,
@@ -1363,7 +1368,7 @@ def generate(
             logits_processor=logits_processor,
         )
 
-        # 9. prepare stopping criteria
+        # 10. prepare stopping criteria
         stopping_criteria = self._get_stopping_criteria(
             generation_config=generation_config, stopping_criteria=stopping_criteria
         )
@@ -1375,7 +1380,7 @@ def generate(
                     f"but is {generation_config.num_return_sequences}."
                 )
 
-            # 8. run greedy search
+            # 11. run greedy search
             outputs = self.greedy_search(
                 input_ids,
                 logits_processor=logits_processor,
@@ -1389,7 +1394,7 @@ def generate(
             )
 
         elif is_sample_gen_mode:
-            # 9. prepare logits warper
+            # 11. prepare logits warper
             logits_warper = self._get_logits_warper(generation_config)
 
             # expand input_ids with `num_return_sequences` additional sequences per batch
@@ -1399,7 +1404,7 @@ def generate(
                 **model_kwargs,
             )
 
-            # 10. run sample
+            # 12. run sample
             outputs = self.sample(
                 input_ids,
                 logits_processor=logits_processor,
@@ -2378,7 +2383,12 @@ def generate(
             and generation_config.do_sample is True
         )
 
-        # 8. prepare distribution pre_processing samplers
+        # 8. prepare batched CFG externally (to enable coexistance with the unbatched CFG)
+        if generation_config.guidance_scale is not None and generation_config.guidance_scale > 1:
+            logits_processor.append(ClassifierFreeGuidanceLogitsProcessor(generation_config.guidance_scale))
+            generation_config.guidance_scale = None
+
+        # 9. prepare distribution pre_processing samplers
         logits_processor = self._get_logits_processor(
             generation_config=generation_config,
             input_ids_seq_length=input_ids_seq_length,
@@ -2387,7 +2397,7 @@ def generate(
             logits_processor=logits_processor,
         )
 
-        # 9. prepare stopping criteria
+        # 10. prepare stopping criteria
         stopping_criteria = self._get_stopping_criteria(
             generation_config=generation_config, stopping_criteria=stopping_criteria
         )
@@ -2399,7 +2409,7 @@ def generate(
                     f"but is {generation_config.num_return_sequences}."
                 )
 
-            # 10. run greedy search
+            # 11. run greedy search
             outputs = self.greedy_search(
                 input_ids,
                 logits_processor=logits_processor,