diff --git a/README.md b/README.md
index f53052d9..3c767128 100644
--- a/README.md
+++ b/README.md
@@ -276,6 +276,7 @@ Over 50 models have been optimized/verified on `ipex-llm`, including *LLaMA/LLaM
 | Qwen1.5 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen1.5) | [link](python/llm/example/GPU/HuggingFace/LLM/qwen1.5) |
 | Qwen2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen2) | [link](python/llm/example/GPU/HuggingFace/LLM/qwen2) |
 | Qwen-VL    | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen-vl)   | [link](python/llm/example/GPU/HuggingFace/Multimodal/qwen-vl)    |
+| Qwen2-Audio    |  | [link](python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio)    |
 | Aquila     | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila)    | [link](python/llm/example/GPU/HuggingFace/LLM/aquila)     |
 | Aquila2     | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila2)    | [link](python/llm/example/GPU/HuggingFace/LLM/aquila2)     |
 | MOSS       | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/moss)      |    | 
diff --git a/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/README.md b/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/README.md
new file mode 100644
index 00000000..b201467a
--- /dev/null
+++ b/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/README.md
@@ -0,0 +1,127 @@
+# Qwen2-Audio
+In this directory, you will find examples on how you could apply IPEX-LLM INT4 optimizations on Qwen2-Audio models on [Intel GPUs](../../../README.md). For illustration purposes, we utilize [Qwen/Qwen2-Audio-7B-Instruct](https://huggingface.co/Qwen/Qwen2-Audio-7B-Instruct) as reference model.
+
+## 0. Requirements
+To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../README.md#requirements) for more information.
+
+
+## Example: Predict Tokens using `generate()` API
+In the example [generate.py](./generate.py), we show a basic use case for a Qwen2-Audio model to conduct transcription using `processor` API, then use the recoginzed text as the input for Qwen2-Audio model to perform an English-Chinese translation using `generate()` API, with IPEX-LLM INT4 optimizations on Intel GPUs.
+### 1. Install
+
+> [!NOTE]
+> Qwen2-Audio requires minimal `transformers` version of 4.35.0, which is not yet released. Currently, you can install the latest version of `transformers` from GitHub. When such a version is released, you can install it using `pip install transformers==4.35.0`.
+
+#### 1.1 Installation on Linux
+We suggest using conda to manage environment:
+```bash
+conda create -n llm python=3.11
+conda activate llm
+# below command will install intel_extension_for_pytorch==2.1.10+xpu as default
+pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+
+pip install librosa
+pip install git+https://github.com/huggingface/transformers
+```
+
+#### 1.2 Installation on Windows
+We suggest using conda to manage environment:
+```bash
+conda create -n llm python=3.11 libuv
+conda activate llm
+
+# below command will install intel_extension_for_pytorch==2.1.10+xpu as default
+pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+
+pip install librosa
+pip install git+https://github.com/huggingface/transformers
+```
+
+### 2. Configures OneAPI environment variables for Linux
+
+> [!NOTE]
+> Skip this step if you are running on Windows.
+
+This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI.
+
+```bash
+source /opt/intel/oneapi/setvars.sh
+```
+
+### 3. Runtime Configurations
+For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
+#### 3.1 Configurations for Linux
+<details>
+
+<summary>For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series</summary>
+
+```bash
+export USE_XETLA=OFF
+export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+export SYCL_CACHE_PERSISTENT=1
+```
+
+</details>
+
+<details>
+
+<summary>For Intel Data Center GPU Max Series</summary>
+
+```bash
+export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
+export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+export SYCL_CACHE_PERSISTENT=1
+export ENABLE_SDP_FUSION=1
+```
+> Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
+</details>
+
+<details>
+
+<summary>For Intel iGPU</summary>
+
+```bash
+export SYCL_CACHE_PERSISTENT=1
+export BIGDL_LLM_XMX_DISABLED=1
+```
+
+</details>
+
+#### 3.2 Configurations for Windows
+<details>
+
+<summary>For Intel iGPU</summary>
+
+```cmd
+set SYCL_CACHE_PERSISTENT=1
+set BIGDL_LLM_XMX_DISABLED=1
+```
+
+</details>
+
+<details>
+
+<summary>For Intel Arc™ A-Series Graphics</summary>
+
+```cmd
+set SYCL_CACHE_PERSISTENT=1
+```
+
+</details>
+
+> [!NOTE]
+> For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile.
+### 4. Running examples
+
+```
+python ./generate.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH
+```
+
+Arguments info:
+- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Qwen2-Audio model (e.g. `Qwen/Qwen2-Audio-7B-Instruct`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'Qwen/Qwen2-Audio-7B-Instruct'`.
+
+#### Sample Output
+In `generate.py`, [an audio clip](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav) is used as the input, which asks the model to translate an English sentence into Chinese. The response from the model is expected to be similar to:
+```bash
+['每个人都希望被赏识，所以如果你欣赏某人，不要保密。']
+```
diff --git a/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/generate.py b/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/generate.py
new file mode 100644
index 00000000..fd186f3e
--- /dev/null
+++ b/python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio/generate.py
@@ -0,0 +1,75 @@
+#
+# Copyright 2016 The BigDL Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import argparse
+from io import BytesIO
+from urllib.request import urlopen
+import librosa
+import torch
+from transformers import Qwen2AudioForConditionalGeneration, AutoProcessor
+from ipex_llm import optimize_model
+
+def main(args):
+    model_path = args.repo_id_or_model_path
+    max_length = args.max_length
+    audio_url = args.audio_url
+
+    processor = AutoProcessor.from_pretrained(model_path)
+    model = Qwen2AudioForConditionalGeneration.from_pretrained(model_path)
+    model = optimize_model(model, low_bit='sym_int4', optimize_llm=True)
+    model = model.half().to('xpu')
+
+    conversation = [
+        {"role": "user", "content": [
+            {"type": "audio", "audio_url": audio_url},
+        ]},
+    ]
+    text = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=False)
+    audios = []
+    for message in conversation:
+        if isinstance(message["content"], list):
+            for ele in message["content"]:
+                if ele["type"] == "audio":
+                    audios.append(librosa.load(
+                        BytesIO(urlopen(ele['audio_url']).read()),
+                        sr=processor.feature_extractor.sampling_rate)[0]
+                    )
+
+    inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
+    inputs = inputs.to('xpu')
+
+    with torch.inference_mode():
+        generate_ids = model.generate(**inputs, max_length=max_length) # warmup
+        import time
+        st = time.time()
+        generate_ids = model.generate(**inputs, max_length=max_length)
+        generate_ids = generate_ids[:, inputs.input_ids.size(1):]
+        et = time.time()
+        print(f'Inference time: {et-st} s')
+
+    response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)
+    print(response)
+
+if __name__=="__main__":
+    parser = argparse.ArgumentParser(description="Qwen2-Audio")
+    parser.add_argument('--repo-id-or-model-path', type=str, default="Qwen/Qwen2-Audio-7B-Instruct",
+                        help='The huggingface repo id for the Qwen2-Audio model checkpoint')
+    parser.add_argument('--max-length', type=int, default=256,
+                        help='The max length of input text')
+    parser.add_argument('--audio-url', type=str, default="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav",
+                        help='The URL to the input audio file')
+    args = parser.parse_args()
+    main(args)