diff --git a/swarms/models/vllm.py b/swarms/models/vllm.py
new file mode 100644
index 00000000..e69de29b
diff --git a/swarms/utils/ray_traceback_wrapper.py b/swarms/utils/ray_traceback_wrapper.py
new file mode 100644
index 00000000..650356cc
--- /dev/null
+++ b/swarms/utils/ray_traceback_wrapper.py
@@ -0,0 +1,91 @@
+import subprocess
+from typing import Optional, Tuple, List
+from swarms.models.base_llm import AbstractLLM
+
+try:
+    from vllm import LLM, SamplingParams
+except ImportError as error:
+    print(f"[ERROR] [vLLM] {error}")
+    subprocess.run(["pip", "install", "vllm"])
+    raise error
+
+
+class vLLM(AbstractLLM):
+    """vLLM model
+
+
+    Args:
+        model_name (str, optional): _description_. Defaults to "facebook/opt-13b".
+        tensor_parallel_size (int, optional): _description_. Defaults to 4.
+        trust_remote_code (bool, optional): _description_. Defaults to False.
+        revision (str, optional): _description_. Defaults to None.
+        temperature (float, optional): _description_. Defaults to 0.5.
+        top_p (float, optional): _description_. Defaults to 0.95.
+        *args: _description_.
+        **kwargs: _description_.
+
+    Methods:
+        run: run the vLLM model
+
+    Raises:
+        error: _description_
+
+    Examples:
+    >>> from swarms.models.vllm import vLLM
+    >>> vllm = vLLM()
+    >>> vllm.run("Hello world!")
+
+
+    """
+
+    def __init__(
+        self,
+        model_name: str = "facebook/opt-13b",
+        tensor_parallel_size: int = 4,
+        trust_remote_code: bool = False,
+        revision: str = None,
+        temperature: float = 0.5,
+        top_p: float = 0.95,
+        *args,
+        **kwargs,
+    ):
+        super().__init__(*args, **kwargs)
+        self.model_name = model_name
+        self.tensor_parallel_size = tensor_parallel_size
+        self.trust_remote_code = trust_remote_code
+        self.revision = revision
+        self.top_p = top_p
+
+        # LLM model
+        self.llm = LLM(
+            model_name=self.model_name,
+            tensor_parallel_size=self.tensor_parallel_size,
+            trust_remote_code=self.trust_remote_code,
+            revision=self.revision,
+            *args,
+            **kwargs,
+        )
+
+        # Sampling parameters
+        self.sampling_params = SamplingParams(
+            temperature=temperature, top_p=top_p, *args, **kwargs
+        )
+
+    def run(self, task: str = None, *args, **kwargs):
+        """Run the vLLM model
+
+        Args:
+            task (str, optional): _description_. Defaults to None.
+
+        Raises:
+            error: _description_
+
+        Returns:
+            _type_: _description_
+        """
+        try:
+            outputs = self.llm.generate(task, self.sampling_params)
+            return outputs
+        except Exception as error:
+            print(f"[ERROR] [vLLM] [run] {error}")
+            raise error
diff --git a/tests/models/test_vllm.py b/tests/models/test_vllm.py
new file mode 100644
index 00000000..d15a13b9
--- /dev/null
+++ b/tests/models/test_vllm.py
@@ -0,0 +1,141 @@
+import pytest
+from swarms.models.vllm import vLLM
+
+
+# Fixture for initializing vLLM
+@pytest.fixture
+def vllm_instance():
+    return vLLM()
+
+
+# Test the default initialization of vLLM
+def test_vllm_default_init(vllm_instance):
+    assert isinstance(vllm_instance, vLLM)
+    assert vllm_instance.model_name == "facebook/opt-13b"
+    assert vllm_instance.tensor_parallel_size == 4
+    assert not vllm_instance.trust_remote_code
+    assert vllm_instance.revision is None
+    assert vllm_instance.temperature == 0.5
+    assert vllm_instance.top_p == 0.95
+
+
+# Test custom initialization of vLLM
+def test_vllm_custom_init():
+    vllm_instance = vLLM(
+        model_name="custom_model",
+        tensor_parallel_size=8,
+        trust_remote_code=True,
+        revision="123",
+        temperature=0.7,
+        top_p=0.9,
+    )
+    assert isinstance(vllm_instance, vLLM)
+    assert vllm_instance.model_name == "custom_model"
+    assert vllm_instance.tensor_parallel_size == 8
+    assert vllm_instance.trust_remote_code
+    assert vllm_instance.revision == "123"
+    assert vllm_instance.temperature == 0.7
+    assert vllm_instance.top_p == 0.9
+
+
+# Test the run method of vLLM
+def test_vllm_run(vllm_instance):
+    task = "Hello, vLLM!"
+    result = vllm_instance.run(task)
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test run method with different temperature and top_p values
+@pytest.mark.parametrize(
+    "temperature, top_p", [(0.2, 0.8), (0.8, 0.2)]
+)
+def test_vllm_run_with_params(vllm_instance, temperature, top_p):
+    task = "Temperature and Top-P Test"
+    result = vllm_instance.run(
+        task, temperature=temperature, top_p=top_p
+    )
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test run method with a specific model revision
+def test_vllm_run_with_revision(vllm_instance):
+    task = "Specific Model Revision Test"
+    result = vllm_instance.run(task, revision="abc123")
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test run method with a specific model name
+def test_vllm_run_with_custom_model(vllm_instance):
+    task = "Custom Model Test"
+    custom_model_name = "my_custom_model"
+    result = vllm_instance.run(task, model_name=custom_model_name)
+    assert isinstance(result, str)
+    assert len(result) > 0
+    assert vllm_instance.model_name == custom_model_name
+
+
+# Test run method with invalid task input
+def test_vllm_run_invalid_task(vllm_instance):
+    invalid_task = None
+    with pytest.raises(ValueError):
+        vllm_instance.run(invalid_task)
+
+
+# Test run method with a very high temperature value
+def test_vllm_run_high_temperature(vllm_instance):
+    task = "High Temperature Test"
+    high_temperature = 10.0
+    result = vllm_instance.run(task, temperature=high_temperature)
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test run method with a very low top_p value
+def test_vllm_run_low_top_p(vllm_instance):
+    task = "Low Top-P Test"
+    low_top_p = 0.01
+    result = vllm_instance.run(task, top_p=low_top_p)
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test run method with an empty task
+def test_vllm_run_empty_task(vllm_instance):
+    empty_task = ""
+    result = vllm_instance.run(empty_task)
+    assert isinstance(result, str)
+    assert len(result) == 0
+
+
+# Test initialization with invalid parameters
+def test_vllm_invalid_init():
+    with pytest.raises(ValueError):
+        vllm_instance = vLLM(
+            model_name=None,
+            tensor_parallel_size=-1,
+            trust_remote_code="invalid",
+            revision=123,
+            temperature=-0.1,
+            top_p=1.1,
+        )
+
+
+# Test running vLLM with a large number of parallel heads
+def test_vllm_large_parallel_heads():
+    vllm_instance = vLLM(tensor_parallel_size=16)
+    task = "Large Parallel Heads Test"
+    result = vllm_instance.run(task)
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+# Test running vLLM with trust_remote_code set to True
+def test_vllm_trust_remote_code():
+    vllm_instance = vLLM(trust_remote_code=True)
+    task = "Trust Remote Code Test"
+    result = vllm_instance.run(task)
+    assert isinstance(result, str)
+    assert len(result) > 0