diff --git a/lib/crewai/src/crewai/llm.py b/lib/crewai/src/crewai/llm.py
index 8a4ac2edd..a48dc647a 100644
--- a/lib/crewai/src/crewai/llm.py
+++ b/lib/crewai/src/crewai/llm.py
@@ -2150,12 +2150,83 @@ class LLM(BaseLLM):
                 "Please remove response_format or use a supported model."
             )
 
+    def _is_ollama_model(self) -> bool:
+        """Check if the model uses an Ollama provider.
+
+        Returns:
+            True if the model string indicates an Ollama provider.
+        """
+        model_lower = self.model.lower()
+        return model_lower.startswith(("ollama/", "ollama_chat/"))
+
+    def _get_ollama_base_url(self) -> str | None:
+        """Get the base URL for the Ollama server.
+
+        Returns the configured api_base or base_url if set, otherwise None
+        (indicating the default localhost would be used by litellm).
+
+        Returns:
+            The Ollama server base URL, or None if not explicitly configured.
+        """
+        return self.api_base or self.base_url
+
+    def _check_ollama_function_calling(self) -> bool:
+        """Query a remote Ollama server to check if the model supports function calling.
+
+        This is used as a fallback when litellm's built-in check fails because it
+        cannot reach a remote Ollama server (it defaults to localhost:11434).
+
+        Returns:
+            True if the remote Ollama model supports function calling (tools), False otherwise.
+        """
+        ollama_url = self._get_ollama_base_url()
+        if not ollama_url:
+            return False
+
+        # Extract the model name without the provider prefix
+        model_name = self.model
+        if "/" in model_name:
+            model_name = model_name.split("/", 1)[1]
+
+        try:
+            url = f"{ollama_url.rstrip('/')}/api/show"
+            response = httpx.post(url, json={"name": model_name}, timeout=5.0)
+            if response.status_code == 200:
+                data = response.json()
+                # Check model capabilities/template for tool support
+                model_info = data.get("model_info", {})
+                template = data.get("template", "")
+
+                # Check if any key in model_info contains tool-related capabilities
+                for key, value in model_info.items():
+                    if "tool" in key.lower() and value is True:
+                        return True
+
+                # Check if the template mentions tools
+                if "tools" in template.lower() or ".ToolCalls" in template:
+                    return True
+
+            return False
+        except Exception as e:
+            logging.debug(f"Failed to query remote Ollama for function calling support: {e!s}")
+            return False
+
     def supports_function_calling(self) -> bool:
         try:
             provider = self._get_custom_llm_provider()
-            return litellm.utils.supports_function_calling(
+            result = litellm.utils.supports_function_calling(
                 self.model, custom_llm_provider=provider
             )
+            if result:
+                return True
+
+            # Fallback: For Ollama models with a remote base_url, litellm's check
+            # fails because it tries to query localhost:11434. Query the remote
+            # Ollama server directly instead.
+            if self._is_ollama_model() and self._get_ollama_base_url():
+                return self._check_ollama_function_calling()
+
+            return False
         except Exception as e:
             logging.error(f"Failed to check function calling support: {e!s}")
             return False
diff --git a/lib/crewai/src/crewai/utilities/internal_instructor.py b/lib/crewai/src/crewai/utilities/internal_instructor.py
index 06a95d234..a0898bcf8 100644
--- a/lib/crewai/src/crewai/utilities/internal_instructor.py
+++ b/lib/crewai/src/crewai/utilities/internal_instructor.py
@@ -124,6 +124,26 @@ class InternalInstructor(Generic[T]):
         pydantic_model = self.to_pydantic()
         return pydantic_model.model_dump_json(indent=2)
 
+    def _get_llm_extra_kwargs(self) -> dict[str, Any]:
+        """Extract extra keyword arguments from the LLM for forwarding to litellm.
+
+        This ensures that provider-specific parameters like api_base and base_url
+        are forwarded to litellm completion calls, which is critical for remote
+        providers (e.g., remote Ollama servers).
+
+        Returns:
+            A dict of extra keyword arguments to pass to the completion call.
+        """
+        if self.llm is None or isinstance(self.llm, str):
+            return {}
+
+        extra: dict[str, Any] = {}
+        for attr in ("api_base", "base_url", "api_key"):
+            value = getattr(self.llm, attr, None)
+            if value is not None:
+                extra[attr] = value
+        return extra
+
     def to_pydantic(self) -> T:
         """Generate structured output using the specified Pydantic model.
 
@@ -145,6 +165,9 @@ class InternalInstructor(Generic[T]):
         else:
             model_name = self.llm.model
 
+        extra_kwargs = self._get_llm_extra_kwargs()
+
         return self._client.chat.completions.create(  # type: ignore[no-any-return]
-            model=model_name, response_model=self.model, messages=messages
+            model=model_name, response_model=self.model, messages=messages,
+            **extra_kwargs,
         )
diff --git a/lib/crewai/tests/test_remote_ollama.py b/lib/crewai/tests/test_remote_ollama.py
new file mode 100644
index 000000000..0d87a2aa9
--- /dev/null
+++ b/lib/crewai/tests/test_remote_ollama.py
@@ -0,0 +1,458 @@
+"""Tests for remote Ollama server support (Issue #4694).
+
+Bug 1: InternalInstructor.to_pydantic() doesn't forward api_base/base_url to litellm.
+Bug 2: LLM.supports_function_calling() doesn't query remote Ollama for capabilities.
+"""
+
+from unittest.mock import Mock, patch
+
+import httpx
+from pydantic import BaseModel
+import pytest
+
+from crewai.llm import LLM
+from crewai.utilities.internal_instructor import InternalInstructor
+
+
+class SimpleModel(BaseModel):
+    name: str
+    age: int
+
+
+# =====================================================================
+# Bug 1: InternalInstructor forwards api_base/base_url to litellm
+# =====================================================================
+
+
+def _make_instructor_bypass_init(llm: object) -> "InternalInstructor[SimpleModel]":
+    """Create an InternalInstructor bypassing __init__ to avoid instructor import.
+
+    This is useful for testing helper methods without needing to mock instructor.
+    """
+    inst: InternalInstructor[SimpleModel] = object.__new__(InternalInstructor)
+    inst.content = "test"
+    inst.model = SimpleModel
+    inst.llm = llm
+    inst.agent = None
+    inst._client = Mock()
+    return inst
+
+
+class TestInternalInstructorForwardsApiBase:
+    """Test that InternalInstructor passes api_base/base_url to litellm completion."""
+
+    def _make_litellm_instructor(
+        self, mock_llm: Mock, mock_client: Mock
+    ) -> "InternalInstructor[SimpleModel]":
+        """Create an InternalInstructor with litellm path, mock client injected."""
+        inst = _make_instructor_bypass_init(mock_llm)
+        inst._client = mock_client
+        return inst
+
+    def test_to_pydantic_forwards_api_base(self) -> None:
+        """When LLM has api_base set, it should be forwarded to the create() call."""
+        mock_llm = Mock()
+        mock_llm.model = "ollama_chat/mistral-small3.2:24b"
+        mock_llm.api_base = "http://remote-server:11434"
+        mock_llm.base_url = None
+        mock_llm.api_key = None
+
+        mock_client = Mock()
+        mock_client.chat.completions.create.return_value = SimpleModel(
+            name="Test", age=25
+        )
+
+        inst = self._make_litellm_instructor(mock_llm, mock_client)
+        result = inst.to_pydantic()
+
+        assert isinstance(result, SimpleModel)
+        assert result.name == "Test"
+        assert result.age == 25
+
+        # Verify api_base was forwarded
+        call_kwargs = mock_client.chat.completions.create.call_args
+        assert call_kwargs.kwargs.get("api_base") == "http://remote-server:11434"
+
+    def test_to_pydantic_forwards_base_url(self) -> None:
+        """When LLM has base_url set, it should be forwarded to the create() call."""
+        mock_llm = Mock()
+        mock_llm.model = "ollama/mistral-small3.2:24b"
+        mock_llm.api_base = None
+        mock_llm.base_url = "http://remote-server:11434"
+        mock_llm.api_key = None
+
+        mock_client = Mock()
+        mock_client.chat.completions.create.return_value = SimpleModel(
+            name="Test", age=30
+        )
+
+        inst = self._make_litellm_instructor(mock_llm, mock_client)
+        result = inst.to_pydantic()
+
+        assert isinstance(result, SimpleModel)
+        call_kwargs = mock_client.chat.completions.create.call_args
+        assert call_kwargs.kwargs.get("base_url") == "http://remote-server:11434"
+
+    def test_to_pydantic_forwards_api_key(self) -> None:
+        """When LLM has api_key set, it should be forwarded to the create() call."""
+        mock_llm = Mock()
+        mock_llm.model = "ollama/mistral-small3.2:24b"
+        mock_llm.api_base = "http://remote-server:11434"
+        mock_llm.base_url = None
+        mock_llm.api_key = "test-key-123"
+
+        mock_client = Mock()
+        mock_client.chat.completions.create.return_value = SimpleModel(
+            name="Test", age=35
+        )
+
+        inst = self._make_litellm_instructor(mock_llm, mock_client)
+        result = inst.to_pydantic()
+
+        call_kwargs = mock_client.chat.completions.create.call_args
+        assert call_kwargs.kwargs.get("api_base") == "http://remote-server:11434"
+        assert call_kwargs.kwargs.get("api_key") == "test-key-123"
+
+    def test_to_pydantic_no_extra_kwargs_for_string_llm(self) -> None:
+        """When LLM is a string, no extra kwargs should be passed."""
+        mock_client = Mock()
+        mock_client.chat.completions.create.return_value = SimpleModel(
+            name="Test", age=20
+        )
+
+        inst = _make_instructor_bypass_init("openai/gpt-4o")
+        inst._client = mock_client
+        inst.to_pydantic()
+
+        call_kwargs = mock_client.chat.completions.create.call_args
+        # No extra kwargs should be present for string LLM
+        assert "api_base" not in (call_kwargs.kwargs or {})
+        assert "base_url" not in (call_kwargs.kwargs or {})
+        assert "api_key" not in (call_kwargs.kwargs or {})
+
+    def test_to_pydantic_no_extra_kwargs_when_none(self) -> None:
+        """When LLM has no api_base/base_url/api_key, no extra kwargs should be passed."""
+        mock_llm = Mock()
+        mock_llm.model = "gpt-4o"
+        mock_llm.api_base = None
+        mock_llm.base_url = None
+        mock_llm.api_key = None
+
+        mock_client = Mock()
+        mock_client.chat.completions.create.return_value = SimpleModel(
+            name="Test", age=40
+        )
+
+        inst = self._make_litellm_instructor(mock_llm, mock_client)
+        inst.to_pydantic()
+
+        call_kwargs = mock_client.chat.completions.create.call_args
+        assert "api_base" not in (call_kwargs.kwargs or {})
+        assert "base_url" not in (call_kwargs.kwargs or {})
+        assert "api_key" not in (call_kwargs.kwargs or {})
+
+
+class TestGetLlmExtraKwargs:
+    """Test the _get_llm_extra_kwargs helper method."""
+
+    def test_returns_empty_for_none_llm(self) -> None:
+        inst = _make_instructor_bypass_init(llm=None)
+        assert inst._get_llm_extra_kwargs() == {}
+
+    def test_returns_empty_for_string_llm(self) -> None:
+        inst = _make_instructor_bypass_init(llm="gpt-4o")
+        assert inst._get_llm_extra_kwargs() == {}
+
+    def test_returns_api_base_when_set(self) -> None:
+        mock_llm = Mock()
+        mock_llm.api_base = "http://remote:11434"
+        mock_llm.base_url = None
+        mock_llm.api_key = None
+
+        inst = _make_instructor_bypass_init(llm=mock_llm)
+        extra = inst._get_llm_extra_kwargs()
+        assert extra == {"api_base": "http://remote:11434"}
+
+    def test_returns_multiple_attrs_when_set(self) -> None:
+        mock_llm = Mock()
+        mock_llm.api_base = "http://remote:11434"
+        mock_llm.base_url = "http://remote:11434"
+        mock_llm.api_key = "secret"
+
+        inst = _make_instructor_bypass_init(llm=mock_llm)
+        extra = inst._get_llm_extra_kwargs()
+        assert extra == {
+            "api_base": "http://remote:11434",
+            "base_url": "http://remote:11434",
+            "api_key": "secret",
+        }
+
+
+# =====================================================================
+# Bug 2: LLM.supports_function_calling() with remote Ollama
+# =====================================================================
+
+
+class TestIsOllamaModel:
+    """Test the _is_ollama_model helper method."""
+
+    def test_ollama_prefix(self) -> None:
+        llm = LLM(model="ollama/mistral-small3.2:24b", is_litellm=True)
+        assert llm._is_ollama_model() is True
+
+    def test_ollama_chat_prefix(self) -> None:
+        llm = LLM(model="ollama_chat/mistral-small3.2:24b", is_litellm=True)
+        assert llm._is_ollama_model() is True
+
+    def test_non_ollama_model(self) -> None:
+        llm = LLM(model="gpt-4o", is_litellm=True)
+        assert llm._is_ollama_model() is False
+
+    def test_openai_model(self) -> None:
+        llm = LLM(model="openai/gpt-4o", is_litellm=True)
+        assert llm._is_ollama_model() is False
+
+
+class TestGetOllamaBaseUrl:
+    """Test the _get_ollama_base_url helper method."""
+
+    def test_returns_api_base(self) -> None:
+        llm = LLM(
+            model="ollama/mistral",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+        assert llm._get_ollama_base_url() == "http://remote:11434"
+
+    def test_returns_base_url(self) -> None:
+        llm = LLM(
+            model="ollama/mistral",
+            base_url="http://remote:11434",
+            is_litellm=True,
+        )
+        assert llm._get_ollama_base_url() == "http://remote:11434"
+
+    def test_api_base_takes_precedence(self) -> None:
+        llm = LLM(
+            model="ollama/mistral",
+            api_base="http://api-base:11434",
+            base_url="http://base-url:11434",
+            is_litellm=True,
+        )
+        assert llm._get_ollama_base_url() == "http://api-base:11434"
+
+    def test_returns_none_when_not_set(self) -> None:
+        llm = LLM(model="ollama/mistral", is_litellm=True)
+        assert llm._get_ollama_base_url() is None
+
+
+class TestCheckOllamaFunctionCalling:
+    """Test the _check_ollama_function_calling method."""
+
+    def test_returns_true_when_tool_key_in_model_info(self) -> None:
+        """Remote Ollama returns model_info with tool-related capability."""
+        llm = LLM(
+            model="ollama/mistral-small3.2:24b",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {
+                "general.architecture": "mistral",
+                "mistral.tool_call": True,
+            },
+            "template": "",
+        }
+
+        with patch("httpx.post", return_value=mock_response) as mock_post:
+            result = llm._check_ollama_function_calling()
+            assert result is True
+            mock_post.assert_called_once_with(
+                "http://remote:11434/api/show",
+                json={"name": "mistral-small3.2:24b"},
+                timeout=5.0,
+            )
+
+    def test_returns_true_when_tools_in_template(self) -> None:
+        """Remote Ollama returns template mentioning tools."""
+        llm = LLM(
+            model="ollama_chat/mistral-small3.2:24b",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {},
+            "template": "{{- if .ToolCalls }}\n[TOOL_CALLS]{{ range .ToolCalls }}",
+        }
+
+        with patch("httpx.post", return_value=mock_response):
+            assert llm._check_ollama_function_calling() is True
+
+    def test_returns_true_when_tools_keyword_in_template(self) -> None:
+        """Remote Ollama returns template with 'tools' keyword."""
+        llm = LLM(
+            model="ollama/qwen2.5:32b",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {},
+            "template": "{{- if .Tools }}\nAvailable tools:\n{{ range .Tools }}",
+        }
+
+        with patch("httpx.post", return_value=mock_response):
+            assert llm._check_ollama_function_calling() is True
+
+    def test_returns_false_when_no_tool_support(self) -> None:
+        """Remote Ollama model without tool support."""
+        llm = LLM(
+            model="ollama/llama2",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {"general.architecture": "llama"},
+            "template": "{{ .Prompt }}",
+        }
+
+        with patch("httpx.post", return_value=mock_response):
+            assert llm._check_ollama_function_calling() is False
+
+    def test_returns_false_when_no_base_url(self) -> None:
+        """When no base URL is configured, should return False."""
+        llm = LLM(model="ollama/mistral", is_litellm=True)
+        assert llm._check_ollama_function_calling() is False
+
+    def test_returns_false_on_connection_error(self) -> None:
+        """When the remote server is unreachable, should return False."""
+        llm = LLM(
+            model="ollama/mistral",
+            api_base="http://unreachable:11434",
+            is_litellm=True,
+        )
+
+        with patch("httpx.post", side_effect=httpx.ConnectError("Connection refused")):
+            assert llm._check_ollama_function_calling() is False
+
+    def test_returns_false_on_404(self) -> None:
+        """When the remote server returns 404, should return False."""
+        llm = LLM(
+            model="ollama/mistral",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 404
+
+        with patch("httpx.post", return_value=mock_response):
+            assert llm._check_ollama_function_calling() is False
+
+    def test_strips_trailing_slash_from_url(self) -> None:
+        """Trailing slash in api_base should be stripped."""
+        llm = LLM(
+            model="ollama/mistral",
+            api_base="http://remote:11434/",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {"mistral.tool_call": True},
+            "template": "",
+        }
+
+        with patch("httpx.post", return_value=mock_response) as mock_post:
+            llm._check_ollama_function_calling()
+            mock_post.assert_called_once_with(
+                "http://remote:11434/api/show",
+                json={"name": "mistral"},
+                timeout=5.0,
+            )
+
+
+class TestSupportsFunctionCallingWithRemoteOllama:
+    """Test the full supports_function_calling flow with remote Ollama."""
+
+    def test_litellm_returns_true_no_fallback_needed(self) -> None:
+        """When litellm says the model supports function calling, use that."""
+        llm = LLM(model="gpt-4o", is_litellm=True)
+        with patch(
+            "litellm.utils.supports_function_calling", return_value=True
+        ):
+            assert llm.supports_function_calling() is True
+
+    def test_remote_ollama_fallback_when_litellm_returns_false(self) -> None:
+        """When litellm returns False for Ollama with remote URL, query the server."""
+        llm = LLM(
+            model="ollama_chat/mistral-small3.2:24b",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {"mistral.tool_call": True},
+            "template": "",
+        }
+
+        with patch("litellm.utils.supports_function_calling", return_value=False):
+            with patch("httpx.post", return_value=mock_response):
+                assert llm.supports_function_calling() is True
+
+    def test_no_fallback_for_non_ollama_models(self) -> None:
+        """When litellm returns False for non-Ollama models, don't use fallback."""
+        llm = LLM(model="gpt-3.5-turbo", is_litellm=True)
+
+        with patch("litellm.utils.supports_function_calling", return_value=False):
+            assert llm.supports_function_calling() is False
+
+    def test_no_fallback_without_remote_url(self) -> None:
+        """Ollama model without remote URL shouldn't trigger fallback."""
+        llm = LLM(model="ollama/mistral", is_litellm=True)
+
+        with patch("litellm.utils.supports_function_calling", return_value=False):
+            assert llm.supports_function_calling() is False
+
+    def test_fallback_returns_false_when_model_lacks_tools(self) -> None:
+        """Ollama model that doesn't support tools returns False even with fallback."""
+        llm = LLM(
+            model="ollama/llama2",
+            api_base="http://remote:11434",
+            is_litellm=True,
+        )
+
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "model_info": {"general.architecture": "llama"},
+            "template": "{{ .Prompt }}",
+        }
+
+        with patch("litellm.utils.supports_function_calling", return_value=False):
+            with patch("httpx.post", return_value=mock_response):
+                assert llm.supports_function_calling() is False
+
+    def test_exception_handling(self) -> None:
+        """When litellm raises an exception, should return False gracefully."""
+        llm = LLM(model="ollama/mistral", api_base="http://remote:11434", is_litellm=True)
+
+        with patch(
+            "litellm.utils.supports_function_calling",
+            side_effect=Exception("Unexpected error"),
+        ):
+            assert llm.supports_function_calling() is False