diff --git a/docs/open_source/setting_up/index.md b/docs/open_source/setting_up/index.md
index 0a0e3fe2c2..923b706a15 100644
--- a/docs/open_source/setting_up/index.md
+++ b/docs/open_source/setting_up/index.md
@@ -149,6 +149,34 @@ giskard.llm.set_llm_model("gemini/gemini-1.5-pro")
 giskard.llm.set_embedding_model("gemini/text-embedding-004")
 ```
 
+## Groq Client Setup
+
+More information on [Groq LiteLLM documentation](https://docs.litellm.ai/docs/providers/groq)
+
+**Note: Groq does not currently support embedding models.**  
+For a complete list of supported embedding providers, see: [LiteLLM Embedding Documentation](https://docs.litellm.ai/docs/embedding/supported_embedding)
+
+### Setup using .env variables
+
+```python
+import os
+import giskard
+
+os.environ["GROQ_API_KEY"] = "" # "my-groq-api-key"
+
+# Optional, setup a model (default LLM is llama-3.3-70b-versatile)
+giskard.llm.set_llm_model("groq/llama-3.3-70b-versatile")
+```
+
+### Setup using completion params
+
+```python
+import giskard
+
+api_key = "" # "my-groq-api-key"
+giskard.llm.set_llm_model("groq/llama-3.3-70b-versatile", api_key=api_key)
+```
+
 ## Custom Client Setup
 
 More information on [Custom Format LiteLLM documentation](https://docs.litellm.ai/docs/providers/custom_llm_server)
diff --git a/giskard/llm/client/groq_client.py b/giskard/llm/client/groq_client.py
new file mode 100644
index 0000000000..676e56dc8a
--- /dev/null
+++ b/giskard/llm/client/groq_client.py
@@ -0,0 +1,97 @@
+from typing import Optional, Sequence
+
+import logging
+from dataclasses import asdict
+
+from ..config import LLMConfigurationError
+from ..errors import LLMImportError
+from . import LLMClient
+from .base import ChatMessage
+
+try:
+    import groq
+    from groq import Groq
+except ImportError as err:
+    raise LLMImportError(flavor="llm") from err
+
+AUTH_ERROR_MESSAGE = (
+    "Could not authenticate with Groq API. Please make sure you have configured the API key by "
+    "setting GROQ_API_KEY in the environment."
+)
+
+JSON_MODE_GUIDANCE = (
+    "To use JSON mode, make sure:\n"
+    "1. Pass format='json' or format='json_object' to the `complete()` method.\n"
+    "2. You describe the expected JSON structure clearly in the system prompt.\n"
+    "3. The selected model supports JSON output.\n"
+    "See: https://console.groq.com/docs/text-chat#json-mode"
+)
+
+logger = logging.getLogger(__name__)
+
+
+class GroqClient(LLMClient):
+    def __init__(
+        self,
+        model: str = "llama-3.3-70b-versatile",  # Default model for Groq
+        client: Groq = None,
+        # json_mode: Optional[bool] = None
+    ):
+        logger.info(f"Initializing GroqClient with model: {model}")
+        self.model = model
+        self._client = client or Groq()
+        logger.info("GroqClient initialized successfully")
+
+    def get_config(self) -> dict:
+        """Return the configuration of the LLM client."""
+        return {"client_type": self.__class__.__name__, "model": self.model}
+
+    def complete(
+        self,
+        messages: Sequence[ChatMessage],
+        temperature: float = 1.0,
+        max_tokens: Optional[int] = None,
+        caller_id: Optional[str] = None,
+        seed: Optional[int] = None,
+        format: Optional[str] = None,
+    ) -> ChatMessage:
+        logger.info(f"GroqClient.complete called with model: {self.model}")
+        logger.info(f"Messages: {messages}")
+
+        extra_params = dict()
+
+        extra_params["seed"] = seed
+
+        if format in {"json", "json_object"}:
+            extra_params["response_format"] = {"type": "json_object"}
+
+        try:
+            completion = self._client.chat.completions.create(
+                model=self.model,
+                messages=[asdict(m) for m in messages],
+                temperature=temperature,
+                max_tokens=max_tokens,
+                **extra_params,
+            )
+
+        except groq.AuthenticationError as err:
+            raise LLMConfigurationError(AUTH_ERROR_MESSAGE) from err
+
+        except groq.BadRequestError as err:
+            if format in {"json", "json_object"}:
+                raise LLMConfigurationError(
+                    f"Model '{self.model}' does not support JSON output or the request format is incorrect.\n\n{JSON_MODE_GUIDANCE}"
+                ) from err
+            raise
+
+        self.logger.log_call(
+            prompt_tokens=completion.usage.prompt_tokens,
+            sampled_tokens=completion.usage.completion_tokens,
+            model=self.model,
+            client_class=self.__class__.__name__,
+            caller_id=caller_id,
+        )
+
+        msg = completion.choices[0].message
+
+        return ChatMessage(role=msg.role, content=msg.content)
diff --git a/pdm.lock b/pdm.lock
index eaae3cd8e6..256693aa02 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -5,7 +5,7 @@
 groups = ["default", "dev", "doc", "llm", "ml-runtime", "talk", "tensorflow", "test"]
 strategy = ["inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:ef9cf680c4ef622a45aaf1e9ece2f196174abdb67bd24b8dab2e75ba45c5629b"
+content_hash = "sha256:ecf506f7488c98a088ba47f54c1c97c2c1117d0bfa4be2993907c5346452ba08"
 
 [[metadata.targets]]
 requires_python = ">=3.9,<3.13"
@@ -34,7 +34,7 @@ files = [
 
 [[package]]
 name = "aiohttp"
-version = "3.12.12"
+version = "3.12.13"
 requires_python = ">=3.9"
 summary = "Async http client/server framework (asyncio)"
 groups = ["dev", "llm", "ml-runtime", "test"]
@@ -49,75 +49,75 @@ dependencies = [
     "yarl<2.0,>=1.17.0",
 ]
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 [[package]]
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 summary = "A database migration tool for SQLAlchemy."
 groups = ["dev", "ml-runtime"]
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 summary = "Low-level, data-driven core of boto 3."
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 summary = "Python package for providing Mozilla's CA Bundle."
 groups = ["default", "dev", "doc", "llm", "ml-runtime", "talk", "tensorflow", "test"]
 files = [
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+version = "7.9.1"
 requires_python = ">=3.9"
 summary = "Code coverage measurement for Python"
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 summary = "Faker is a Python package that generates fake data for you."
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 [[package]]
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 requires_python = ">=3.7"
 summary = "Google API client core library"
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 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
@@ -5625,17 +5630,18 @@ files = [
 
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 summary = "Pytest plugin for measuring coverage."
 groups = ["test"]
 dependencies = [
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 [[package]]
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 ]
 
+[[package]]
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+version = "3.14.1"
+requires_python = ">=3.8"
+summary = "Thin-wrapper around the mock package for easier use with pytest"
+groups = ["test"]
+dependencies = [
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 summary = "Simple, modern and high performance file watching and code reload in python."
 groups = ["doc"]
@@ -8052,65 +8068,69 @@ dependencies = [
     "anyio>=3.0.0",
 ]
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 ]
 
 [[package]]
diff --git a/pyproject.toml b/pyproject.toml
index a92b9f4349..001febb8c5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -189,6 +189,7 @@ llm = [
     "umap-learn>=0.5.5",
     "scikit-learn>=1.3.2",
     "litellm<1.66.0",
+    "groq>=0.10.0",
 ]
 
 talk = [
@@ -322,4 +323,4 @@ env = ["WANDB_MODE=disabled"]
 
 [tool.deptry]
 extend_exclude = [".history"]
-ignore_notebooks = true
+ignore_notebooks = true
\ No newline at end of file
diff --git a/tests/llm/test_llm_client.py b/tests/llm/test_llm_client.py
index 714bfb5849..04f2521e3f 100644
--- a/tests/llm/test_llm_client.py
+++ b/tests/llm/test_llm_client.py
@@ -1,4 +1,5 @@
 import json
+from importlib.util import find_spec
 from unittest.mock import MagicMock, Mock, patch
 
 import pydantic
@@ -11,6 +12,7 @@
 from giskard.llm.client import ChatMessage
 from giskard.llm.client.bedrock import ClaudeBedrockClient
 from giskard.llm.client.gemini import GeminiClient
+from giskard.llm.client.groq_client import GroqClient
 from giskard.llm.client.openai import OpenAIClient
 
 PYDANTIC_V2 = pydantic.__version__.startswith("2.")
@@ -238,3 +240,38 @@ def test_gemini_client():
     # Assert that the response is a ChatMessage and has the correct content
     assert isinstance(res, ChatMessage)
     assert res.content == "This is a test!"
+
+
+# Check if groq is installed
+has_groq = find_spec("groq") is not None
+
+
+@pytest.mark.skipif(not PYDANTIC_V2 or not has_groq, reason="Groq client test requires Pydantic v2 and groq package")
+def test_groq_client():
+    # Mock the Groq response
+    demo_response = Mock()
+    demo_response.usage = Mock(prompt_tokens=13, completion_tokens=7)
+    demo_response.choices = [Mock(message=Mock(role="assistant", content="This is a test!"))]
+
+    # Mock the Groq client
+    mock_client = Mock()
+    mock_client.chat.completions.create.return_value = demo_response
+
+    client = GroqClient(model="llama-3.3-70b-versatile", client=mock_client)
+
+    # Call the complete method
+    res = client.complete([ChatMessage(role="user", content="Hello")], temperature=0.7, format="json", max_tokens=100)
+
+    # Assert json_object format was passed
+    assert mock_client.chat.completions.create.call_args[1]["response_format"] == {"type": "json_object"}
+
+    # Assert that create was called with correct arguments
+    mock_client.chat.completions.create.assert_called_once()
+    assert mock_client.chat.completions.create.call_args[1]["messages"] == [{"role": "user", "content": "Hello"}]
+    assert mock_client.chat.completions.create.call_args[1]["temperature"] == 0.7
+    assert mock_client.chat.completions.create.call_args[1]["max_tokens"] == 100
+    assert mock_client.chat.completions.create.call_args[1]["model"] == "llama-3.3-70b-versatile"
+
+    # Assert the response is correct
+    assert isinstance(res, ChatMessage)
+    assert res.content == "This is a test!"