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Merge pull request #35324 from BerriAI/litellm_gpt56_pricing_test_gaps

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test(pricing): cover gpt-5.6 cache-cost plumbing and bedrock_mantle responses billing
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Mateo Wang 2026-07-30 22:23:27 -07:00 • committed by GitHub
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43
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
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@ -709,6 +709,49 @@ def test_generic_cost_per_token_gpt56_flex_above_272k(
assert completion_cost == pytest.approx(standard_long_completion_cost / 2)
@pytest.mark.parametrize(
"service_tier,prompt_tokens,input_rate,cache_write_rate,cache_read_rate",
[
(None, 100000, 2e-6, 2.5e-6, 2e-7),
("flex", 100000, 1e-6, 1.25e-6, 1e-7),
("priority", 100000, 4e-6, 5e-6, 4e-7),
(None, 300000, 4e-6, 5e-6, 4e-7),
("flex", 300000, 2e-6, 2.5e-6, 2e-7),
],
)
def test_generic_cost_per_token_gpt56_terra_cache_costs_by_tier_and_context(
service_tier, prompt_tokens, input_rate, cache_write_rate, cache_read_rate
):
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
cached_tokens = 50000
cache_write_tokens = 40000
text_tokens = prompt_tokens - cached_tokens - cache_write_tokens
usage = Usage(
prompt_tokens=prompt_tokens,
completion_tokens=100,
total_tokens=prompt_tokens + 100,
prompt_tokens_details=PromptTokensDetailsWrapper(
cached_tokens=cached_tokens, cache_write_tokens=cache_write_tokens
),
)
prompt_cost, _ = generic_cost_per_token(
model="gpt-5.6-terra",
usage=usage,
custom_llm_provider="openai",
service_tier=service_tier,
)
expected_prompt_cost = (
text_tokens * input_rate
+ cached_tokens * cache_read_rate
+ cache_write_tokens * cache_write_rate
)
assert prompt_cost == pytest.approx(expected_prompt_cost)
@pytest.mark.parametrize(
"model,input_cost,output_cost,cache_read_cost",
[

33
tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py
View file

@ -1534,6 +1534,39 @@ class TestBedrockMantleResponsesPricing:
assert info["output_cost_per_token"] == pytest.approx(output_cost)
assert info["max_input_tokens"] == 272000
@pytest.mark.parametrize(
"model, input_cost, output_cost",
[
("openai.gpt-5.6-sol", 5.5e-06, 3.3e-05),
("openai.gpt-5.6-terra", 2.2e-06, 1.32e-05),
("openai.gpt-5.6-luna", 2.2e-07, 1.32e-06),
],
)
def test_gpt_5_6_responses_call_cost(self, local_cost_map, model, input_cost, output_cost):
from litellm.types.llms.openai import ResponseAPIUsage, ResponsesAPIResponse
input_tokens = 100000
output_tokens = 10000
response = ResponsesAPIResponse(
id="resp-1",
created_at=1700000000,
model=model,
output=[],
usage=ResponseAPIUsage(
input_tokens=input_tokens,
output_tokens=output_tokens,
total_tokens=input_tokens + output_tokens,
),
)
cost = litellm.completion_cost(
completion_response=response,
model=f"bedrock_mantle/{model}",
custom_llm_provider="bedrock_mantle",
)
assert cost == pytest.approx(input_tokens * input_cost + output_tokens * output_cost)
def test_models_registered(self, local_cost_map):
assert "bedrock_mantle/openai.gpt-5.5" in litellm.bedrock_mantle_models
assert "bedrock_mantle/openai.gpt-5.4" in litellm.bedrock_mantle_models