diff --git a/llama_stack/providers/remote/inference/ollama/ollama.py b/llama_stack/providers/remote/inference/ollama/ollama.py
index 944493b6d..dc2c8b3f5 100644
--- a/llama_stack/providers/remote/inference/ollama/ollama.py
+++ b/llama_stack/providers/remote/inference/ollama/ollama.py
@@ -5,10 +5,11 @@
 # the root directory of this source tree.
 
 
-from typing import Any, AsyncGenerator, List, Optional, Union
+from typing import Any, AsyncGenerator, Dict, List, Optional, Union
 
 import httpx
 from ollama import AsyncClient
+from openai import AsyncOpenAI
 
 from llama_stack.apis.common.content_types import (
     ImageContentItem,
@@ -38,6 +39,7 @@ from llama_stack.apis.inference import (
     ToolDefinition,
     ToolPromptFormat,
 )
+from llama_stack.apis.inference.inference import OpenAIChatCompletion, OpenAICompletion, OpenAIMessageParam
 from llama_stack.apis.models import Model, ModelType
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ModelsProtocolPrivate
@@ -45,10 +47,8 @@ from llama_stack.providers.utils.inference.model_registry import (
     ModelRegistryHelper,
 )
 from llama_stack.providers.utils.inference.openai_compat import (
-    OpenAIChatCompletionUnsupportedMixin,
     OpenAICompatCompletionChoice,
     OpenAICompatCompletionResponse,
-    OpenAICompletionUnsupportedMixin,
     get_sampling_options,
     process_chat_completion_response,
     process_chat_completion_stream_response,
@@ -70,8 +70,6 @@ logger = get_logger(name=__name__, category="inference")
 
 
 class OllamaInferenceAdapter(
-    OpenAICompletionUnsupportedMixin,
-    OpenAIChatCompletionUnsupportedMixin,
     Inference,
     ModelsProtocolPrivate,
 ):
@@ -83,6 +81,10 @@ class OllamaInferenceAdapter(
     def client(self) -> AsyncClient:
         return AsyncClient(host=self.url)
 
+    @property
+    def openai_client(self) -> AsyncOpenAI:
+        return AsyncOpenAI(base_url=f"{self.url}/v1", api_key="ollama")
+
     async def initialize(self) -> None:
         logger.info(f"checking connectivity to Ollama at `{self.url}`...")
         try:
@@ -326,6 +328,110 @@ class OllamaInferenceAdapter(
 
         return model
 
+    async def openai_completion(
+        self,
+        model: str,
+        prompt: str,
+        best_of: Optional[int] = None,
+        echo: Optional[bool] = None,
+        frequency_penalty: Optional[float] = None,
+        logit_bias: Optional[Dict[str, float]] = None,
+        logprobs: Optional[bool] = None,
+        max_tokens: Optional[int] = None,
+        n: Optional[int] = None,
+        presence_penalty: Optional[float] = None,
+        seed: Optional[int] = None,
+        stop: Optional[Union[str, List[str]]] = None,
+        stream: Optional[bool] = None,
+        stream_options: Optional[Dict[str, Any]] = None,
+        temperature: Optional[float] = None,
+        top_p: Optional[float] = None,
+        user: Optional[str] = None,
+    ) -> OpenAICompletion:
+        model_obj = await self._get_model(model)
+        params = {
+            k: v
+            for k, v in {
+                "model": model_obj.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,
+            }.items()
+            if v is not None
+        }
+        return await self.openai_client.completions.create(**params)  # type: ignore
+
+    async def openai_chat_completion(
+        self,
+        model: str,
+        messages: List[OpenAIMessageParam],
+        frequency_penalty: Optional[float] = None,
+        function_call: Optional[Union[str, Dict[str, Any]]] = None,
+        functions: Optional[List[Dict[str, Any]]] = None,
+        logit_bias: Optional[Dict[str, float]] = None,
+        logprobs: Optional[bool] = None,
+        max_completion_tokens: Optional[int] = None,
+        max_tokens: Optional[int] = None,
+        n: Optional[int] = None,
+        parallel_tool_calls: Optional[bool] = None,
+        presence_penalty: Optional[float] = None,
+        response_format: Optional[Dict[str, str]] = None,
+        seed: Optional[int] = None,
+        stop: Optional[Union[str, List[str]]] = None,
+        stream: Optional[bool] = None,
+        stream_options: Optional[Dict[str, Any]] = None,
+        temperature: Optional[float] = None,
+        tool_choice: Optional[Union[str, Dict[str, Any]]] = None,
+        tools: Optional[List[Dict[str, Any]]] = None,
+        top_logprobs: Optional[int] = None,
+        top_p: Optional[float] = None,
+        user: Optional[str] = None,
+    ) -> OpenAIChatCompletion:
+        model_obj = await self._get_model(model)
+        params = {
+            k: v
+            for k, v in {
+                "model": model_obj.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,
+            }.items()
+            if v is not None
+        }
+        return await self.openai_client.chat.completions.create(**params)  # type: ignore
+
 
 async def convert_message_to_openai_dict_for_ollama(message: Message) -> List[dict]:
     async def _convert_content(content) -> dict: