diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_fw_models_metadata.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_fw_models_metadata.py
index 1b2ca298694..c8365e7b7c0 100644
--- a/tests/test_litellm/llms/azure_ai/test_azure_ai_fw_models_metadata.py
+++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_fw_models_metadata.py
@@ -38,37 +38,6 @@ def use_local_model_cost_map():
         monkeypatch.undo()
 
 
-@pytest.mark.parametrize(
-    "model_name,expected_prompt,expected_completion",
-    [
-        ("FW-Kimi-K2.6", 1.045, 4.4),
-        ("FW-DeepSeek-V4-Pro", 1.925, 3.828),
-        ("FW-GLM-5.2", 1.54, 4.84),
-        ("FW-Kimi-K3", 3.3, 16.5),
-        ("FW-MiniMax-M2.5", 0.33, 1.32),
-        ("FW-Inkling", 1.0, 4.05),
-        ("FW-Nemotron-3-Ultra-NVFP4", 0.6, 2.4),
-        ("FW-Nemotron-Lightning-3.5-30B-A3B", 0.06, 0.22),
-    ],
-)
-def test_azure_ai_fw_cost_per_token(
-    use_local_model_cost_map, model_name, expected_prompt, expected_completion
-):
-    from litellm.llms.azure_ai.cost_calculator import cost_per_token
-    from litellm.types.utils import Usage
-
-    usage = Usage(
-        prompt_tokens=1_000_000,
-        completion_tokens=1_000_000,
-        total_tokens=2_000_000,
-    )
-
-    prompt_cost, completion_cost = cost_per_token(model=model_name, usage=usage)
-
-    assert prompt_cost == pytest.approx(expected_prompt)
-    assert completion_cost == pytest.approx(expected_completion)
-
-
 def test_azure_ai_fw_nemotron_lightning_supports_tool_choice(use_local_model_cost_map):
     from litellm.llms.azure_ai.chat.transformation import AzureAIStudioConfig
 
diff --git a/tests/test_litellm/proxy/spend_tracking/test_savings.py b/tests/test_litellm/proxy/spend_tracking/test_savings.py
index f90d5daf768..615938f2e33 100644
--- a/tests/test_litellm/proxy/spend_tracking/test_savings.py
+++ b/tests/test_litellm/proxy/spend_tracking/test_savings.py
@@ -356,29 +356,6 @@ def test_openai_style_cache_write_tokens_are_netted_out():
     )
 
 
-def test_sub_input_cache_write_price_is_an_extra_saving():
-    """A few models price writes below input; there the premium is a real credit.
-
-    Clamping the premium at zero would silently undercount these, so the subtraction
-    stays signed. ``azure/eu/gpt-4o-2024-11-20`` ships a write price at ~0.5x input.
-    """
-    model = "azure/eu/gpt-4o-2024-11-20"
-    info = litellm.get_model_info(model=model)
-    input_cost = info["input_cost_per_token"]
-    cheap_write = info["cache_creation_input_token_cost"]
-    assert 0 < cheap_write < input_cost, "fixture drifted: this test needs a model pricing cache writes below input"
-
-    result = compute_savings_spend(
-        model=model,
-        custom_llm_provider=None,
-        compression_saved_tokens=0,
-        gateway_injected_cache=True,
-        usage_object=_caching_usage(read=1000, written=4000),
-    )
-    assert result.prompt_caching == pytest.approx(4000 * (input_cost - cheap_write))
-    assert result.prompt_caching > 0
-
-
 def test_negative_cache_write_count_clamps_to_zero():
     """A malformed negative write count must not be read as a saving."""
     input_cost, cache_read_cost = _anthropic_costs("claude-sonnet-5")