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fix(cost): preserve zero hourly cache write rates in pricing tiers (#45545)

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tin-berri 2026-10-09 15:29:37 -07:00 • committed by GitHub
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2 changed files with 56 additions and 23 deletions
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6
litellm/litellm_core_utils/llm_cost_calc/utils.py
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@ -401,8 +401,10 @@ def _get_tiered_base_costs(model_info: ModelInfo, usage: Usage) -> tuple[float,
tier_rate(tier, "input_cost_per_token"),
completion_cost,
cache_creation_cost,
tier_rate(tier, "cache_creation_input_token_cost_above_1hr", "cache_creation_input_token_cost")
or cache_creation_cost,
tier_rate(tier, "cache_creation_input_token_cost_above_1hr")
if "cache_creation_input_token_cost_above_1hr" in tier
and tier["cache_creation_input_token_cost_above_1hr"] is not None
else cache_creation_cost,
tier_rate(tier, "cache_read_input_token_cost", "input_cost_per_token"),
)

73
tests/unit/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -1437,21 +1437,47 @@ def test_generic_cost_per_token_tier_without_cache_rates_bills_cache_at_the_tier
litellm.model_cost.pop(model, None)
def test_generic_cost_per_token_tier_without_a_1hr_cache_rate_bills_the_tier_cache_creation_rate():
model = "litellm-test-tiered-no-1hr-cache-rate"
custom_llm_provider = "openrouter"
@pytest.mark.parametrize(
("cache_rates", "expected_write_rate"),
[
pytest.param({"cache_creation_input_token_cost": 3.0}, 3.0, id="missing-hourly"),
pytest.param(
{"cache_creation_input_token_cost": 3.0, "cache_creation_input_token_cost_above_1hr": None},
3.0,
id="null-hourly",
),
pytest.param(
{"cache_creation_input_token_cost": 3.0, "cache_creation_input_token_cost_above_1hr": 0.0},
0.0,
id="free-hourly",
),
pytest.param(
{"cache_creation_input_token_cost": 3.0, "cache_creation_input_token_cost_above_1hr": 5.0},
5.0,
id="priced-hourly",
),
pytest.param({"cache_creation_input_token_cost": 0.0}, 0.0, id="free-ordinary"),
pytest.param({}, 1.0, id="missing-both"),
],
)
@pytest.mark.parametrize("one_hour_tokens", [10, 20])
def test_generic_cost_per_token_tier_1hr_cache_rate_preserves_zero_and_fallback(
cache_rates: Mapping[str, float | None], expected_write_rate: float, one_hour_tokens: int
) -> None:
model: Final = "litellm-test-tiered-1hr-cache-rate"
litellm.register_model(
{
model: {
"litellm_provider": custom_llm_provider,
"litellm_provider": "openrouter",
"mode": "chat",
"cache_creation_input_token_cost_above_1hr": 9e-05,
"cache_creation_input_token_cost_above_1hr": 9.0,
"tiered_pricing": [
{
"range": [0, 128000],
"input_cost_per_token": 7e-07,
"output_cost_per_token": 3.5e-06,
"cache_creation_input_token_cost": 8.75e-07,
"input_cost_per_token": 1.0,
"output_cost_per_token": 2.0,
"cache_read_input_token_cost": 0.1,
**cache_rates,
}
],
}
@ -1459,27 +1485,32 @@ def test_generic_cost_per_token_tier_without_a_1hr_cache_rate_bills_the_tier_cac
)
try:
usage = Usage(
prompt_tokens=1000,
usage: Final = Usage(
prompt_tokens=100,
completion_tokens=10,
total_tokens=1010,
total_tokens=110,
prompt_tokens_details=PromptTokensDetailsWrapper(
cache_creation_tokens=800,
cached_tokens=40,
cache_creation_tokens=20,
cache_creation_token_details=CacheCreationTokenDetails(
ephemeral_5m_input_tokens=300, ephemeral_1h_input_tokens=500
ephemeral_5m_input_tokens=20 - one_hour_tokens, ephemeral_1h_input_tokens=one_hour_tokens
),
),
)
prompt_cost, completion_cost = generic_cost_per_token(
model=model,
usage=usage,
custom_llm_provider=custom_llm_provider,
costs: Final = generic_cost_per_token(model=model, usage=usage, custom_llm_provider="openrouter")
breakdown: Final = get_token_type_cost_breakdown(
model=model, usage=usage, custom_llm_provider="openrouter"
)
tier_cache_creation_rate = 8.75e-07
expected_prompt = (200 * 7e-07) + (800 * tier_cache_creation_rate)
assert round(prompt_cost, 12) == round(expected_prompt, 12)
assert round(completion_cost, 12) == round(10 * 3.5e-06, 12)
ordinary_rate: Final = cache_rates.get("cache_creation_input_token_cost")
expected_write_cost: Final = (
(20 - one_hour_tokens) * (ordinary_rate if ordinary_rate is not None else 1.0)
+ one_hour_tokens * expected_write_rate
)
assert costs == pytest.approx((40 * 1.0 + 40 * 0.1 + expected_write_cost, 10 * 2.0))
assert breakdown.cache_creation_cost == pytest.approx(expected_write_cost)
assert breakdown.rates is not None
assert breakdown.rates.cache_creation_input_token_cost_above_1hr == expected_write_rate
finally:
litellm.model_cost.pop(model, None)