diff --git a/tests/unit/test_cost_calculator.py b/tests/unit/test_cost_calculator.py
index 49d51e99790..6de368fbf00 100644
--- a/tests/unit/test_cost_calculator.py
+++ b/tests/unit/test_cost_calculator.py
@@ -11645,68 +11645,3 @@ def test_upstream_cost_header_total_on_an_unmapped_alias_is_split_by_the_served_
     input_share: Final = (10 * 0.001) / (10 * 0.001 + 20 * 0.002)
     assert breakdown["input_cost"] == pytest.approx(0.25 * input_share)
     assert breakdown["output_cost"] == pytest.approx(0.25 * (1 - input_share))
-
-
-_PER_CALL_RATES: Final = MappingProxyType({"input_cost_per_token": 2e-06, "output_cost_per_token": 4e-06})
-
-
-def _per_call_priced_reply(model: str, usage_extras: Mapping[str, str]) -> ModelResponse:
-    usage: Final = Usage(prompt_tokens=1000, completion_tokens=1000, total_tokens=2000)
-    for field, value in usage_extras.items():
-        setattr(usage, field, value)
-    return ModelResponse(model=model, choices=[Choices(message=Message(content="hi"))], usage=usage)
-
-
-@pytest.mark.parametrize(
-    ("row", "call_kwargs", "usage_extras", "multiplier"),
-    [
-        pytest.param(
-            {"litellm_provider": "openai", "mode": "chat", "regional_processing_uplift_multiplier_eu": 1.25},
-            {
-                "model": "openai/lit-eu-residency-test",
-                "api_key": "fake-key",
-                "api_base": "https://eu.api.openai.com/v1",
-            },
-            {},
-            1.25,
-            id="openai-data-residency",
-        ),
-        pytest.param(
-            {"litellm_provider": "vertex_ai", "mode": "chat", "regional_endpoint_uplift_multiplier": 1.5},
-            {
-                "model": "vertex_ai/lit-regional-endpoint-test",
-                "vertex_project": "lit-project",
-                "vertex_location": "us-east5",
-                "vertex_credentials": "{}",
-            },
-            {},
-            1.5,
-            id="vertex-regional-endpoint",
-        ),
-        pytest.param(
-            {"litellm_provider": "anthropic", "mode": "chat", "provider_specific_entry": {"fast": 2.0}},
-            {"model": "anthropic/lit-fast-mode-test", "api_key": "fake-key"},
-            {"speed": "fast"},
-            2.0,
-            id="anthropic-fast-mode",
-        ),
-    ],
-)
-def test_per_call_custom_prices_keep_the_regional_and_speed_multipliers(
-    monkeypatch: pytest.MonkeyPatch,
-    row: Mapping[str, object],
-    call_kwargs: Mapping[str, str],
-    usage_extras: Mapping[str, str],
-    multiplier: float,
-) -> None:
-    monkeypatch.setitem(litellm.model_cost, call_kwargs["model"], {**row, **_PER_CALL_RATES})
-    _invalidate_model_cost_lowercase_map()
-
-    response: Final = litellm.completion(
-        messages=[{"role": "user", "content": "hello"}],
-        mock_response=_per_call_priced_reply(call_kwargs["model"].split("/", 1)[1], usage_extras),
-        **call_kwargs,
-        **_PER_CALL_RATES,
-    )
-
-    assert response._hidden_params["response_cost"] == pytest.approx((1000 * 2e-06 + 1000 * 4e-06) * multiplier)