diff --git a/llama_stack/providers/remote/inference/openai/openai.py b/llama_stack/providers/remote/inference/openai/openai.py
index 76218e87e..9a1ec7ee0 100644
--- a/llama_stack/providers/remote/inference/openai/openai.py
+++ b/llama_stack/providers/remote/inference/openai/openai.py
@@ -4,12 +4,41 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import logging
+from collections.abc import AsyncIterator
+from typing import Any
+
+from openai import AsyncOpenAI
+
+from llama_stack.apis.inference.inference import (
+    OpenAIChatCompletion,
+    OpenAIChatCompletionChunk,
+    OpenAICompletion,
+    OpenAIMessageParam,
+    OpenAIResponseFormatParam,
+)
 from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
+from llama_stack.providers.utils.inference.openai_compat import prepare_openai_completion_params
 
 from .config import OpenAIConfig
 from .models import MODEL_ENTRIES
 
+logger = logging.getLogger(__name__)
 
+
+#
+# This OpenAI adapter implements Inference methods using two clients -
+#
+# | Inference Method           | Implementation Source    |
+# |----------------------------|--------------------------|
+# | completion                 | LiteLLMOpenAIMixin       |
+# | chat_completion            | LiteLLMOpenAIMixin       |
+# | embedding                  | LiteLLMOpenAIMixin       |
+# | batch_completion           | LiteLLMOpenAIMixin       |
+# | batch_chat_completion      | LiteLLMOpenAIMixin       |
+# | openai_completion          | AsyncOpenAI              |
+# | openai_chat_completion     | AsyncOpenAI              |
+#
 class OpenAIInferenceAdapter(LiteLLMOpenAIMixin):
     def __init__(self, config: OpenAIConfig) -> None:
         LiteLLMOpenAIMixin.__init__(
@@ -26,9 +55,113 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin):
         # if we do not set this, users will be exposed to the
         # litellm specific model names, an abstraction leak.
         self.is_openai_compat = True
+        self._openai_client = AsyncOpenAI(
+            api_key=self.config.api_key,
+        )
 
     async def initialize(self) -> None:
         await super().initialize()
 
     async def shutdown(self) -> None:
         await super().shutdown()
+
+    async def openai_completion(
+        self,
+        model: str,
+        prompt: str | list[str] | list[int] | list[list[int]],
+        best_of: int | None = None,
+        echo: bool | None = None,
+        frequency_penalty: float | None = None,
+        logit_bias: dict[str, float] | None = None,
+        logprobs: bool | None = None,
+        max_tokens: int | None = None,
+        n: int | None = None,
+        presence_penalty: float | None = None,
+        seed: int | None = None,
+        stop: str | list[str] | None = None,
+        stream: bool | None = None,
+        stream_options: dict[str, Any] | None = None,
+        temperature: float | None = None,
+        top_p: float | None = None,
+        user: str | None = None,
+        guided_choice: list[str] | None = None,
+        prompt_logprobs: int | None = None,
+    ) -> OpenAICompletion:
+        if guided_choice is not None:
+            logging.warning("guided_choice is not supported by the OpenAI API. Ignoring.")
+        if prompt_logprobs is not None:
+            logging.warning("prompt_logprobs is not supported by the OpenAI API. Ignoring.")
+
+        params = await prepare_openai_completion_params(
+            model=(await self.model_store.get_model(model)).provider_resource_id,
+            prompt=prompt,
+            best_of=best_of,
+            echo=echo,
+            frequency_penalty=frequency_penalty,
+            logit_bias=logit_bias,
+            logprobs=logprobs,
+            max_tokens=max_tokens,
+            n=n,
+            presence_penalty=presence_penalty,
+            seed=seed,
+            stop=stop,
+            stream=stream,
+            stream_options=stream_options,
+            temperature=temperature,
+            top_p=top_p,
+            user=user,
+        )
+        return await self._openai_client.completions.create(**params)
+
+    async def openai_chat_completion(
+        self,
+        model: str,
+        messages: list[OpenAIMessageParam],
+        frequency_penalty: float | None = None,
+        function_call: str | dict[str, Any] | None = None,
+        functions: list[dict[str, Any]] | None = None,
+        logit_bias: dict[str, float] | None = None,
+        logprobs: bool | None = None,
+        max_completion_tokens: int | None = None,
+        max_tokens: int | None = None,
+        n: int | None = None,
+        parallel_tool_calls: bool | None = None,
+        presence_penalty: float | None = None,
+        response_format: OpenAIResponseFormatParam | None = None,
+        seed: int | None = None,
+        stop: str | list[str] | None = None,
+        stream: bool | None = None,
+        stream_options: dict[str, Any] | None = None,
+        temperature: float | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        top_logprobs: int | None = None,
+        top_p: float | None = None,
+        user: str | None = None,
+    ) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
+        params = await prepare_openai_completion_params(
+            model=(await self.model_store.get_model(model)).provider_resource_id,
+            messages=messages,
+            frequency_penalty=frequency_penalty,
+            function_call=function_call,
+            functions=functions,
+            logit_bias=logit_bias,
+            logprobs=logprobs,
+            max_completion_tokens=max_completion_tokens,
+            max_tokens=max_tokens,
+            n=n,
+            parallel_tool_calls=parallel_tool_calls,
+            presence_penalty=presence_penalty,
+            response_format=response_format,
+            seed=seed,
+            stop=stop,
+            stream=stream,
+            stream_options=stream_options,
+            temperature=temperature,
+            tool_choice=tool_choice,
+            tools=tools,
+            top_logprobs=top_logprobs,
+            top_p=top_p,
+            user=user,
+        )
+        return await self._openai_client.chat.completions.create(**params)