diff --git a/artemis/agents/flash/summarizer.py b/artemis/agents/flash/summarizer.py
index 56c5e098..d8b6a1a4 100644
--- a/artemis/agents/flash/summarizer.py
+++ b/artemis/agents/flash/summarizer.py
@@ -36,7 +36,7 @@
 
 from artemis.context import ArtemisContext
 from artemis.memory.step_memory import JobKey, StepMemoryService
-from artemis.services.llm import RobustChatModelWrapper, get_google_llm, get_llm
+from artemis.services.llm import RobustChatModelWrapper, get_llm, get_node_model
 from artemis.services.token_meter import record_llm_usage
 from artemis.utils.logger import get_logger
 from artemis.utils.task_tree import format_actions_clean
@@ -166,11 +166,15 @@ def __init__(
         self._model_name = target_model
         try:
             if model_name:
-                self._llm = get_google_llm(model_name=target_model, temperature=0.0)
+                self._llm = get_node_model(
+                    ctx, "summarizer", model_name=target_model, is_utils=True, temperature=0.0
+                )
             else:
                 self._llm = get_llm(ctx, name="summarizer", is_utils=True)
         except Exception:
-            self._llm = get_google_llm(model_name=target_model, temperature=0.0)
+            self._llm = get_node_model(
+                ctx, "summarizer", model_name=target_model, is_utils=True, temperature=0.0
+            )
         try:
             configured = getattr(self._llm, "model", None) or getattr(self._llm, "model_name", None)
             if isinstance(configured, str) and configured:
@@ -341,7 +345,7 @@ def _meter_lens_call(self, response: Any) -> None:
         """Meter one raw-model lens call as an ``llm_usage`` trace, best-effort.
 
         Gateway-wrapped models already meter at the wrapper exit; only the raw
-        ``get_google_llm`` bypass needs explicit metering here. Lens prompts
+        ``get_node_model`` bypass needs explicit metering here. Lens prompts
         are tiny and must not overwrite the session's ``last_prompt_tokens``
         (the compaction thresholds' live context base), hence
         ``update_last_prompt=False``.
diff --git a/artemis/memory/chunking.py b/artemis/memory/chunking.py
index 4e564540..741e2045 100644
--- a/artemis/memory/chunking.py
+++ b/artemis/memory/chunking.py
@@ -323,17 +323,23 @@ def __init__(
 
     def _get_llm(self):
         if self._llm is None:
-            from artemis.services.llm import get_google_llm
+            from artemis.services.llm import get_node_model
 
-            self._llm = get_google_llm(model_name=self._model_name, temperature=0.0)
+            self._llm = get_node_model(
+                self._ctx, "summarizer", model_name=self._model_name, is_utils=True, temperature=0.0
+            )
         return self._llm
 
     def _get_fallback_llm(self):
         if self._fallback_llm is None and self._fallback_model_name:
-            from artemis.services.llm import get_google_llm
-
-            self._fallback_llm = get_google_llm(
-                model_name=self._fallback_model_name, temperature=0.0
+            from artemis.services.llm import get_node_model
+
+            self._fallback_llm = get_node_model(
+                self._ctx,
+                "summarizer",
+                model_name=self._fallback_model_name,
+                is_utils=True,
+                temperature=0.0,
             )
         return self._fallback_llm
 
diff --git a/artemis/services/llm.py b/artemis/services/llm.py
index 784e971f..57cfe2ff 100644
--- a/artemis/services/llm.py
+++ b/artemis/services/llm.py
@@ -906,6 +906,36 @@ async def invoke_llm_with_timeout_message[T](
         await asyncio.gather(waiter_task, return_exceptions=True)
 
 
+def get_node_model(
+    ctx: ArtemisContext | None,
+    name: str,
+    *,
+    model_name: str,
+    is_utils: bool = False,
+    temperature: float | None = None,
+) -> BaseChatModel:
+    """Build a raw model for ``name``'s configured provider, overriding only the model.
+
+    Callers that pin a specific lightweight model still have to honour the
+    provider the operator configured. ``get_google_llm`` hard-codes
+    ``ModelProvider.GOOGLE``, so pinning a model there sends an OpenAI-compatible
+    deployment to the Gemini client and fails on an empty ``GOOGLE_API_KEY``.
+
+    Returns a raw model rather than a ``RobustChatModelWrapper``, matching what
+    ``get_google_llm`` returned, so callers keep metering their own calls.
+
+    Without a context there is no configuration to read and no provider to
+    honour, so Google stays the default for that case alone.
+    """
+    if ctx is None:
+        return get_google_llm(model_name=model_name, temperature=temperature)
+    endpoint = _resolve_endpoint(ctx, name, is_utils=is_utils)
+    update: dict[str, Any] = {"model_name": model_name}
+    if temperature is not None:
+        update["temperature"] = temperature
+    return ModelFactory.create_model(endpoint.model_copy(update=update))
+
+
 # Backward compatible factory functions delegating to ModelFactory
 def get_google_llm(
     model_name: str = "gemini-3.8-flash",
diff --git a/tests/unit/test_llm_node_model.py b/tests/unit/test_llm_node_model.py
new file mode 100644
index 00000000..22152e2c
--- /dev/null
+++ b/tests/unit/test_llm_node_model.py
@@ -0,0 +1,107 @@
+"""A pinned lightweight model must still use the operator's configured provider."""
+
+from types import SimpleNamespace
+
+from artemis.llm.router import ModelEndpoint, ModelProvider
+from artemis.services import llm as llm_service
+from artemis.services.llm import get_node_model
+
+
+def _capture(monkeypatch):
+    seen: list[ModelEndpoint] = []
+    monkeypatch.setattr(
+        llm_service.ModelFactory,
+        "create_model",
+        staticmethod(lambda endpoint: seen.append(endpoint) or SimpleNamespace(endpoint=endpoint)),
+    )
+    return seen
+
+
+def _endpoint(provider: ModelProvider) -> ModelEndpoint:
+    return ModelEndpoint(provider=provider, model_name="configured-default", temperature=0.7)
+
+
+def test_pinned_model_keeps_the_configured_openai_provider(monkeypatch):
+    """Issue #138: the Flash summarizer pinned a model and got a Gemini client.
+
+    An OpenAI-compatible deployment then failed on an empty GOOGLE_API_KEY
+    before the first step ran, even though the provider was configured
+    correctly.
+    """
+    seen = _capture(monkeypatch)
+    monkeypatch.setattr(
+        llm_service, "_resolve_endpoint", lambda *a, **k: _endpoint(ModelProvider.OPENAI)
+    )
+
+    get_node_model(
+        SimpleNamespace(), "summarizer", model_name="my-lite", is_utils=True, temperature=0.0
+    )
+
+    assert len(seen) == 1
+    assert seen[0].provider is ModelProvider.OPENAI
+    assert seen[0].model_name == "my-lite"
+    assert seen[0].temperature == 0.0
+
+
+def test_a_google_deployment_is_unaffected(monkeypatch):
+    seen = _capture(monkeypatch)
+    monkeypatch.setattr(
+        llm_service, "_resolve_endpoint", lambda *a, **k: _endpoint(ModelProvider.GOOGLE)
+    )
+
+    get_node_model(SimpleNamespace(), "summarizer", model_name="gemini-lite", is_utils=True)
+
+    assert seen[0].provider is ModelProvider.GOOGLE
+    assert seen[0].model_name == "gemini-lite"
+    # Temperature is left alone when the caller does not pin one.
+    assert seen[0].temperature == 0.7
+
+
+def test_without_a_context_there_is_no_configured_provider_to_honour(monkeypatch):
+    """No context means no config to read, so Google stays the default there."""
+    seen = _capture(monkeypatch)
+
+    get_node_model(None, "summarizer", model_name="gemini-lite", temperature=0.0)
+
+    assert seen[0].provider is ModelProvider.GOOGLE
+    assert seen[0].model_name == "gemini-lite"
+
+
+def test_the_capsule_lens_builds_its_model_on_the_configured_provider(monkeypatch):
+    """The same bypass at its real call site, which is what the issue reports.
+
+    StepCapsuleLens pins its own compression model, so before the fix it built
+    a GOOGLE endpoint no matter what the operator configured. This assertion,
+    not the import, is the one that fails on an unpatched tree.
+    """
+    from artemis.memory.chunking import StepCapsuleLens
+
+    seen = _capture(monkeypatch)
+    monkeypatch.setattr(
+        llm_service, "_resolve_endpoint", lambda *a, **k: _endpoint(ModelProvider.OPENAI)
+    )
+
+    lens = StepCapsuleLens(model_name="my-compressor", ctx=SimpleNamespace())
+    lens._get_llm()
+
+    assert seen[0].provider is ModelProvider.OPENAI, (
+        "a pinned compression model must not force the Gemini client"
+    )
+    assert seen[0].model_name == "my-compressor"
+
+
+def test_the_capsule_lens_fallback_model_follows_the_same_provider(monkeypatch):
+    from artemis.memory.chunking import StepCapsuleLens
+
+    seen = _capture(monkeypatch)
+    monkeypatch.setattr(
+        llm_service, "_resolve_endpoint", lambda *a, **k: _endpoint(ModelProvider.OPENAI)
+    )
+
+    lens = StepCapsuleLens(
+        model_name="my-compressor", fallback_model_name="my-backup", ctx=SimpleNamespace()
+    )
+    lens._get_fallback_llm()
+
+    assert seen[0].provider is ModelProvider.OPENAI
+    assert seen[0].model_name == "my-backup"