diff --git a/src/google/adk/models/_generate_content_body.py b/src/google/adk/models/_generate_content_body.py
new file mode 100644
index 0000000000..06343ddf3d
--- /dev/null
+++ b/src/google/adk/models/_generate_content_body.py
@@ -0,0 +1,132 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Turn an ``LlmRequest`` into a ``generateContent`` request body.
+
+``LlmRequest.config`` is a ``types.GenerateContentConfig``: one flat namespace
+of 35 fields. On the wire those fields go to three different places. Some sit at
+the top level of the request, most belong inside ``generationConfig``, and a few
+mean something only to the client library and are rejected by the endpoint.
+
+Nothing on the type says which is which, and getting it wrong does not raise.
+Bury ``tools`` inside ``generationConfig`` and the call still returns 200 with a
+well formed response in it. The tools are simply absent, so the model answers
+from memory instead of calling anything, and the failure looks like a model that
+chose not to call the tool.
+
+Rather than keep a hand written list of which field goes where, this delegates
+to the same converter ``google-genai`` uses for its own built-in models. A hand
+written list is a second copy of the mapping and it goes stale the moment
+``GenerateContentConfig`` gains a field: every custom ``BaseLlm`` in the wild
+then starts silently dropping that field. Delegating means there is one copy and
+it moves when the type moves.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+from typing import Optional
+
+from google.genai import models as _genai_models
+from google.genai import types
+
+__all__ = ["to_generate_content_body"]
+
+
+class _ApiMode:
+  """The one thing the genai converters need from an API client.
+
+  ``_GenerateContentParameters_to_vertex`` touches exactly one attribute on the
+  client it is handed, ``vertexai``, by way of ``t_model``. Passing a real
+  client works and is preferred when the caller has one. This stands in when the
+  caller does not, so the helper stays usable from a ``BaseLlm`` that talks REST
+  directly and never builds a genai client at all.
+  """
+
+  __slots__ = ("vertexai",)
+
+  def __init__(self, vertexai: bool):
+    self.vertexai = vertexai
+
+
+def to_generate_content_body(
+    llm_request: Any,
+    *,
+    vertexai: bool = True,
+    api_client: Optional[Any] = None,
+) -> dict[str, Any]:
+  """Return the request body for ``llm_request``.
+
+  Args:
+    llm_request: the ``LlmRequest`` to convert.
+    vertexai: whether the body is bound for Vertex AI rather than the Gemini
+      Developer API. The two differ in more than the URL: some config fields
+      exist on one and not the other, so this is not cosmetic. Ignored when
+      ``api_client`` is given.
+    api_client: a genai API client, if the caller has one. Preferred over
+      ``vertexai`` because it is the real thing rather than a stand-in.
+
+  Returns:
+    A dict ready to send as the request body. The model name is not in it; the
+    caller already knows the model, and on Vertex it belongs in the URL.
+
+  Raises:
+    ValueError: if a config field is not valid for the target API. The message
+      names the ``GenerateContentConfig`` field so the error points at the line
+      that set it rather than at the converter.
+  """
+  client = api_client if api_client is not None else _ApiMode(vertexai)
+
+  is_vertex = getattr(client, "vertexai", True)
+
+  params = types._GenerateContentParameters(
+      model=llm_request.model,
+      contents=llm_request.contents,
+      config=llm_request.config,
+  )
+
+  convert = (
+      _genai_models._GenerateContentParameters_to_vertex
+      if is_vertex
+      else _genai_models._GenerateContentParameters_to_mldev
+  )
+
+  try:
+    body = convert(client, params)
+  except ValueError as exc:
+    raise ValueError(_annotate(str(exc), vertexai=is_vertex)) from exc
+
+  # The converters return the model under a private "_url" key, because the
+  # caller is normally the genai client, which uses it to build the path. It is
+  # routing information, not body content. Sending it is a 400.
+  body.pop("_url", None)
+  return body
+
+
+def _annotate(message: str, *, vertexai: bool) -> str:
+  """Point a genai validation error back at the ADK field that caused it.
+
+  The converters raise messages that start with the offending field name, e.g.
+  "enable_enhanced_civic_answers parameter is only supported in ...". That is
+  accurate and still hard to act on from a ``BaseLlm``, because the reader has
+  no reason to connect it to the config they built several layers up.
+  """
+  first = message.split(" ", 1)[0]
+  if first in types.GenerateContentConfig.model_fields:
+    mode = "Vertex AI" if vertexai else "the Gemini Developer API"
+    return (
+        f"{message} (set as LlmRequest.config.{first}; this request targets"
+        f" {mode}.)"
+    )
+  return message
diff --git a/src/google/adk/models/llm_request.py b/src/google/adk/models/llm_request.py
index bf53fad23c..1aa7dd5acd 100644
--- a/src/google/adk/models/llm_request.py
+++ b/src/google/adk/models/llm_request.py
@@ -15,6 +15,7 @@
 from __future__ import annotations
 
 import logging
+from typing import Any
 from typing import Optional
 from typing import Union
 
@@ -399,3 +400,37 @@ def set_output_schema(
 
     self.config.response_schema = schema
     self.config.response_mime_type = "application/json"
+
+  def to_generate_content_body(
+      self,
+      *,
+      vertexai: bool = True,
+      api_client: Optional[Any] = None,
+  ) -> dict[str, Any]:
+    """Returns this request as a ``generateContent`` request body.
+
+    ``config`` is one flat namespace, but its fields go to three different
+    places on the wire. Some sit at the top level, most belong inside
+    ``generationConfig``, and a few are consumed by the client library and
+    rejected by the endpoint. Getting that split wrong does not raise: bury
+    ``tools`` in ``generationConfig`` and the call returns 200 with no function
+    call in it, because none was ever offered.
+
+    Custom ``BaseLlm`` implementations that build their own request body should
+    use this rather than flattening ``config`` by hand.
+
+    Args:
+      vertexai: whether the body is bound for Vertex AI rather than the Gemini
+        Developer API. Ignored when ``api_client`` is given.
+      api_client: a genai API client, if the caller has one.
+
+    Returns:
+      A dict ready to send as the request body.
+    """
+    # Imported here rather than at module scope: this pulls in google.genai's
+    # model converters, which nothing else in this module needs.
+    from ._generate_content_body import to_generate_content_body
+
+    return to_generate_content_body(
+        self, vertexai=vertexai, api_client=api_client
+    )
diff --git a/tests/unittests/models/test_generate_content_body.py b/tests/unittests/models/test_generate_content_body.py
new file mode 100644
index 0000000000..f789038bdc
--- /dev/null
+++ b/tests/unittests/models/test_generate_content_body.py
@@ -0,0 +1,293 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for the LlmRequest -> generateContent body conversion."""
+
+import pytest
+from google.adk.models.llm_request import LlmRequest
+from google.genai import types
+
+from google.adk.models._generate_content_body import to_generate_content_body
+
+# Fields that sit at the top level of a Vertex generateContent request, as of
+# google-genai 2.18.1. This list exists to be asserted against, not to be used:
+# the helper derives the split rather than reading it. If a release moves a
+# field, test_every_config_field_is_classified fails first and names it.
+TOP_LEVEL = {
+    "cachedContent",
+    "labels",
+    "modelArmorConfig",
+    "safetySettings",
+    "serviceTier",
+    "systemInstruction",
+    "toolConfig",
+    "tools",
+}
+
+# Config fields the client library consumes. The endpoint rejects them.
+CLIENT_ONLY = {
+    "httpOptions",
+    "automaticFunctionCalling",
+    "shouldReturnHttpResponse",
+}
+
+
+def _tool() -> types.Tool:
+  return types.Tool(
+      function_declarations=[
+          types.FunctionDeclaration(
+              name="a_tool",
+              description="Look up the weather in a city.",
+              parameters=types.Schema(
+                  type=types.Type.OBJECT,
+                  properties={"city": types.Schema(type=types.Type.STRING)},
+              ),
+          )
+      ]
+  )
+
+
+def _request(**config_kwargs) -> LlmRequest:
+  return LlmRequest(
+      model="gemini-3.5-flash",
+      contents=[types.Content(role="user", parts=[types.Part(text="hi")])],
+      config=types.GenerateContentConfig(**config_kwargs),
+  )
+
+
+def _full_config_kwargs() -> dict:
+  """Every field that can be set at once on a Vertex-bound request.
+
+  Two of the 35 are left out on purpose. response_json_schema is mutually
+  exclusive with response_schema, and enable_enhanced_civic_answers is Developer
+  API only, which test_developer_api_only_field_is_named covers separately.
+  """
+  return dict(
+      system_instruction="You are a research agent.",
+      tools=[_tool()],
+      tool_config=types.ToolConfig(
+          function_calling_config=types.FunctionCallingConfig(mode="AUTO")
+      ),
+      safety_settings=[
+          types.SafetySetting(
+              category="HARM_CATEGORY_HATE_SPEECH", threshold="BLOCK_ONLY_HIGH"
+          )
+      ],
+      cached_content="projects/p/locations/us-central1/cachedContents/123",
+      labels={"team": "research"},
+      http_options=types.HttpOptions(timeout=60_000),
+      automatic_function_calling=types.AutomaticFunctionCallingConfig(
+          disable=True
+      ),
+      should_return_http_response=True,
+      temperature=0.2,
+      top_p=0.9,
+      top_k=40,
+      candidate_count=1,
+      max_output_tokens=8192,
+      stop_sequences=["STOP"],
+      response_logprobs=True,
+      logprobs=3,
+      presence_penalty=0.1,
+      frequency_penalty=0.1,
+      seed=42,
+      response_mime_type="application/json",
+      response_schema=types.Schema(
+          type=types.Type.OBJECT,
+          properties={"answer": types.Schema(type=types.Type.STRING)},
+      ),
+      routing_config=types.GenerationConfigRoutingConfig(
+          auto_mode=types.GenerationConfigRoutingConfigAutoRoutingMode(
+              model_routing_preference="BALANCED"
+          )
+      ),
+      model_selection_config=types.ModelSelectionConfig(
+          feature_selection_preference="BALANCED"
+      ),
+      response_modalities=["TEXT"],
+      media_resolution="MEDIA_RESOLUTION_MEDIUM",
+      speech_config=types.SpeechConfig(
+          voice_config=types.VoiceConfig(
+              prebuilt_voice_config=types.PrebuiltVoiceConfig(voice_name="Kore")
+          )
+      ),
+      audio_timestamp=True,
+      thinking_config=types.ThinkingConfig(
+          include_thoughts=True, thinking_budget=4096
+      ),
+      image_config=types.ImageConfig(aspect_ratio="1:1"),
+      model_armor_config=types.ModelArmorConfig(
+          prompt_template_name="projects/p/locations/us-central1/templates/t"
+      ),
+      service_tier="standard",
+      audio_transcription_config=types.AudioTranscriptionConfig(),
+  )
+
+
+# The bug this whole module exists to prevent.
+def test_tools_are_top_level_not_buried_in_generation_config():
+  body = to_generate_content_body(_request(temperature=0.2, tools=[_tool()]))
+
+  assert "tools" in body
+  assert "tools" not in body["generationConfig"]
+
+
+def test_temperature_stays_in_generation_config():
+  body = to_generate_content_body(_request(temperature=0.2, tools=[_tool()]))
+
+  assert body["generationConfig"]["temperature"] == pytest.approx(0.2)
+  assert "temperature" not in body
+
+
+def test_client_only_fields_never_reach_the_wire():
+  body = to_generate_content_body(
+      _request(
+          temperature=0.2,
+          http_options=types.HttpOptions(timeout=60_000),
+          automatic_function_calling=types.AutomaticFunctionCallingConfig(
+              disable=True
+          ),
+          should_return_http_response=True,
+      )
+  )
+
+  emitted = set(body) | set(body.get("generationConfig", {}))
+  assert not (CLIENT_ONLY & emitted)
+
+
+def test_url_routing_key_is_stripped():
+  # The converter returns the model under "_url" for the genai client to build
+  # a path with. It is not body content and Vertex 400s on it.
+  body = to_generate_content_body(_request(temperature=0.2))
+
+  assert "_url" not in body
+
+
+def test_full_field_set_splits_eight_twentytwo_three():
+  body = to_generate_content_body(_request(**_full_config_kwargs()))
+
+  top = set(body) - {"contents", "generationConfig"}
+  generation = set(body["generationConfig"])
+
+  assert top == TOP_LEVEL
+  assert not (TOP_LEVEL & generation), "a top-level field was buried"
+  assert not (CLIENT_ONLY & (top | generation))
+  # 33 set, 8 up top, 3 dropped, so 22 sampling settings and nothing lost.
+  assert len(generation) == 22
+
+
+def test_model_selection_config_is_renamed_to_model_config():
+  # The only field that changes name in transit. Anyone diffing their own config
+  # keys against the emitted body gets a false miss on this one.
+  body = to_generate_content_body(
+      _request(
+          model_selection_config=types.ModelSelectionConfig(
+              feature_selection_preference="BALANCED"
+          )
+      )
+  )
+
+  assert "modelConfig" in body["generationConfig"]
+  assert "modelSelectionConfig" not in body["generationConfig"]
+
+
+def test_developer_api_only_field_is_named_in_the_error():
+  request = _request(enable_enhanced_civic_answers=True)
+
+  with pytest.raises(ValueError) as excinfo:
+    to_generate_content_body(request, vertexai=True)
+
+  message = str(excinfo.value)
+  assert "enable_enhanced_civic_answers" in message
+  # The point of the annotation: say where it was set, not just that it is bad.
+  assert "LlmRequest.config" in message
+  assert "Vertex AI" in message
+
+
+def test_developer_api_accepts_what_vertex_rejects():
+  body = to_generate_content_body(
+      _request(enable_enhanced_civic_answers=True), vertexai=False
+  )
+
+  assert body is not None
+
+
+def test_string_system_instruction_becomes_a_content_block():
+  body = to_generate_content_body(_request(system_instruction="Be terse."))
+
+  assert body["systemInstruction"]["parts"][0]["text"] == "Be terse."
+
+
+def test_no_config_still_produces_a_body():
+  request = LlmRequest(
+      model="gemini-3.5-flash",
+      contents=[types.Content(role="user", parts=[types.Part(text="hi")])],
+  )
+
+  body = to_generate_content_body(request)
+
+  assert body["contents"][0]["parts"][0]["text"] == "hi"
+
+
+# The test that keeps the other tests honest.
+def test_every_config_field_is_classified():
+  """Fail when GenerateContentConfig gains a field nobody has classified.
+
+  This is the whole argument for the helper. A hand written mapping goes stale
+  silently: the new field lands in generationConfig, the endpoint ignores it,
+  and no one finds out until a feature quietly stops working. This turns that
+  into a red test naming the field.
+  """
+  known = (
+      TOP_LEVEL
+      | CLIENT_ONLY
+      | {"enableEnhancedCivicAnswers", "responseJsonSchema"}
+  )
+  body = to_generate_content_body(_request(**_full_config_kwargs()))
+  classified = (
+      (set(body) - {"contents", "generationConfig"})
+      | set(body["generationConfig"])
+      | known
+  )
+
+  # Aliases as the wire spells them, which is how the body is keyed.
+  declared = {
+      field.alias or name
+      for name, field in types.GenerateContentConfig.model_fields.items()
+  }
+  # modelSelectionConfig is emitted as modelConfig; see the rename test.
+  declared.discard("modelSelectionConfig")
+  classified.add("modelSelectionConfig")
+
+  unclassified = declared - classified
+  assert not unclassified, (
+      "GenerateContentConfig gained field(s) with no known destination:"
+      f" {sorted(unclassified)}. Add them to TOP_LEVEL or CLIENT_ONLY and"
+      " confirm where the converter puts them."
+  )
+
+
+def test_method_matches_function():
+  """LlmRequest.to_generate_content_body is a thin delegate, not a fork."""
+  request = _request(**_full_config_kwargs())
+
+  assert request.to_generate_content_body() == to_generate_content_body(request)
+
+
+def test_method_passes_the_api_mode_through():
+  request = _request(enable_enhanced_civic_answers=True)
+
+  assert request.to_generate_content_body(vertexai=False) is not None
+  with pytest.raises(ValueError):
+    request.to_generate_content_body(vertexai=True)