diff --git a/src/transformers/models/qwen2_audio/modeling_qwen2_audio.py b/src/transformers/models/qwen2_audio/modeling_qwen2_audio.py
index fb9d013eeff3..b4d1f41f3ec2 100644
--- a/src/transformers/models/qwen2_audio/modeling_qwen2_audio.py
+++ b/src/transformers/models/qwen2_audio/modeling_qwen2_audio.py
@@ -19,7 +19,6 @@
 from typing import Callable, Optional, Union
 
 import torch
-import torch.utils.checkpoint
 from torch import nn
 
 from ...activations import ACT2FN
@@ -727,6 +726,7 @@ def forward(
         output_attentions: Optional[bool] = None,
         output_hidden_states: Optional[bool] = None,
         return_dict: Optional[bool] = None,
+        cache_position: Optional[torch.LongTensor] = None,
     ) -> Union[tuple, Qwen2AudioCausalLMOutputWithPast]:
         r"""
         feature_attention_mask (`torch.Tensor` of shape `(batch_size, feature_sequence_length)`):
@@ -845,6 +845,7 @@ def forward(
             output_attentions=output_attentions,
             output_hidden_states=output_hidden_states,
             return_dict=return_dict,
+            cache_position=cache_position,
         )
 
         logits = outputs[0]
@@ -878,5 +879,19 @@ def forward(
             attention_mask=attention_mask,
         )
 
+    def prepare_inputs_for_generation(self, *args, **kwargs):
+        # Overwritten -- we should not pass input_features when we are in cached decoding stage
+
+        input_features = kwargs.pop("input_features", None)
+        cache_position = kwargs.get("cache_position")
+
+        model_inputs = super().prepare_inputs_for_generation(*args, **kwargs)
+
+        if cache_position is not None and cache_position[0] == 0:
+            # input_features should only be passed when we are not in cached decoding stage
+            model_inputs["input_features"] = input_features
+
+        return model_inputs
+
 
 __all__ = ["Qwen2AudioForConditionalGeneration", "Qwen2AudioPreTrainedModel", "Qwen2AudioEncoder"]
diff --git a/tests/models/qwen2_audio/test_modeling_qwen2_audio.py b/tests/models/qwen2_audio/test_modeling_qwen2_audio.py
index 571ac0737081..4533fbbf99d8 100644
--- a/tests/models/qwen2_audio/test_modeling_qwen2_audio.py
+++ b/tests/models/qwen2_audio/test_modeling_qwen2_audio.py
@@ -34,6 +34,7 @@
     torch_device,
 )
 
+from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
 
@@ -132,14 +133,12 @@ def prepare_config_and_inputs_for_common(self):
 
 
 @require_torch
-class Qwen2AudioForConditionalGenerationModelTest(ModelTesterMixin, unittest.TestCase):
+class Qwen2AudioForConditionalGenerationModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
     """
     Model tester for `Qwen2AudioForConditionalGeneration`.
     """
 
     all_model_classes = (Qwen2AudioForConditionalGeneration,) if is_torch_available() else ()
-    # Doesn't run generation tests. TODO eustache/joao: some generation tests are broken, the errors seem cache-related
-    all_generative_model_classes = ()
     test_pruning = False
     test_head_masking = False
     _is_composite = True
diff --git a/tests/test_modeling_common.py b/tests/test_modeling_common.py
index 38c581992b31..754e267662b9 100755
--- a/tests/test_modeling_common.py
+++ b/tests/test_modeling_common.py
@@ -3484,6 +3484,7 @@ def flash_attn_inference_equivalence(self, attn_implementation: str, padding_sid
             model = model_class(config)
 
             model.to(torch_device)
+            model.to(torch.bfloat16)
             dummy_input = inputs_dict[model.main_input_name][:1]
             if dummy_input.dtype in [torch.float32, torch.float16]:
                 dummy_input = dummy_input.to(torch.bfloat16)