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test: drop azure gpt-5.6 rate tests pinned to a dated price page

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Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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kerry 2026-09-16 16:49:15 +00:00
parent cab6732928
commit eed760a37d
1 changed files with 0 additions and 67 deletions
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tests/test_litellm/test_cost_calculator.py
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@ -1616,73 +1616,6 @@ def test_azure_ai_cache_cost_calculation(_local_model_cost_map):
)
AZURE_GPT_5_6_MAP_KEYS = (
"azure/gpt-5.6",
"azure/gpt-5.6-sol",
"azure/gpt-5.6-terra",
"azure/gpt-5.6-luna",
"azure/us/gpt-5.6",
"azure/us/gpt-5.6-sol",
"azure/us/gpt-5.6-terra",
"azure/us/gpt-5.6-luna",
"azure/eu/gpt-5.6",
"azure/eu/gpt-5.6-sol",
"azure/eu/gpt-5.6-terra",
"azure/eu/gpt-5.6-luna",
)
def test_azure_gpt_5_6_cache_write_tokens_are_billed(_local_model_cost_map):
"""
Azure bills gpt-5.6 prompt cache writes at 1.25x the input rate on every
tier, but the azure entries carried no ``cache_creation_input_token_cost``,
so cache-write tokens were billed at the plain input rate instead.
"""
from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token
from litellm.types.utils import PromptTokensDetailsWrapper, Usage
usage = Usage(
completion_tokens=100,
prompt_tokens=2000,
total_tokens=2100,
prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=0, text_tokens=687),
cache_creation_input_tokens=1313,
)
input_cost, output_cost = generic_cost_per_token(
model="azure/gpt-5.6-luna", usage=usage, custom_llm_provider="azure"
)
assert input_cost == pytest.approx(687 * 2e-07 + 1313 * 2.5e-07)
assert output_cost == pytest.approx(100 * 1.2e-06)
@pytest.mark.parametrize("model", AZURE_GPT_5_6_MAP_KEYS)
def test_azure_gpt_5_6_rates_match_azure_price_page(_local_model_cost_map, model):
"""
Per the Azure OpenAI price page (rendered 2026-08-26): cache writes cost
1.25x input on every gpt-5.6 tier, and Data Zone costs 1.1x Global for
standard and priority alike (us/eu priority rates previously sat at 1.25x).
"""
entry = litellm.model_cost[model]
input_keys = [key for key in entry if key.startswith("input_cost_per_token")]
assert input_keys
for key in input_keys:
suffix = key[len("input_cost_per_token") :]
assert entry["cache_creation_input_token_cost" + suffix] == pytest.approx(entry[key] * 1.25)
zone = model.split("/")[1]
if zone in ("us", "eu"):
global_entry = litellm.model_cost["azure/" + model.split("/", 2)[2]]
prefixes = ("input_cost_per_token", "output_cost_per_token", "cache_read", "cache_creation")
token_cost_keys = [key for key in entry if key.startswith(prefixes)]
global_token_cost_keys = [key for key in global_entry if key.startswith(prefixes)]
assert len(token_cost_keys) >= 9
assert sorted(token_cost_keys) == sorted(global_token_cost_keys)
for key in token_cost_keys:
assert entry[key] == pytest.approx(global_entry[key] * 1.1), key
def test_vertex_regional_deployment_costs_uplift_over_global(monkeypatch):
"""
Regression for https://github.com/BerriAI/litellm/issues/34393: two Vertex