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fix(model_prices): correct regional processing uplift to gpt-5.4/5.5 series only (#31136)

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* fix(model_prices): correct regional processing uplift assignment

gpt-4.1, gpt-4o, gpt-5, and their variants were incorrectly carrying
the 10% EU/US regional processing uplift multiplier. Per OpenAI's
pricing docs, the uplift applies only to models released on or after
2026-03-05 (gpt-5.4 series and gpt-5.5 series).

Removes the uplift from: gpt-4.1, gpt-4.1-mini, gpt-4.1-nano,
gpt-4o, gpt-4o-2024-08-06, gpt-4o-2024-11-20, gpt-4o-mini, gpt-5,
gpt-5-pro, gpt-5-mini, gpt-5-nano.

Adds the uplift to: gpt-5.4, gpt-5.4-mini, gpt-5.4-nano, gpt-5.4-pro,
gpt-5.5, gpt-5.5-pro.

* fix(model_prices): apply same regional uplift correction to backup file

* fix(model_prices): add regional uplift to date-versioned gpt-5.4/5.5 siblings

* test(model_prices): update data residency tests to use gpt-5.4 as the uplift model

The tests were using gpt-5 which no longer carries the regional processing
uplift after correcting which models have it. Switch to gpt-5.4 (released
2026-03-05, the cutoff date) and add a regression parametrize covering
all pre-cutoff models to pin that they stay uplift-free.

* test(batches): use gpt-5.4 for data residency uplift assertion

batch_cost_calculator's data residency uplift test still pinned gpt-5,
which no longer carries the regional processing uplift after this change.
Switch it to gpt-5.4 (the canonical post-cutoff uplift model), matching
the llm_cost_calc test update.

---------

Co-authored-by: mgalbato <37748295+mgalbato@users.noreply.github.com>
This commit is contained in:
Mateo Wang 2026-06-23 15:57:26 -07:00 • committed by GitHub
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commit 286169d39b
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4 changed files with 76 additions and 54 deletions
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46
litellm/model_prices_and_context_window_backup.json
View file

@ -20350,8 +20350,6 @@
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"output_cost_per_token_batches": 4e-06,
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@ -20425,8 +20423,6 @@
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@ -20500,8 +20496,6 @@
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@ -20573,8 +20567,6 @@
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@ -20616,8 +20608,6 @@
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@ -20639,8 +20629,6 @@
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@ -22029,6 +22013,8 @@
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@ -22388,6 +22388,8 @@
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@ -22434,6 +22436,8 @@
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@ -22477,6 +22481,8 @@
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@ -22558,8 +22566,6 @@
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@ -22966,8 +22972,6 @@
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@ -23049,8 +23053,6 @@
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"mode": "chat",
"output_cost_per_token": 4e-07,
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46
model_prices_and_context_window.json
View file

@ -20358,8 +20358,6 @@
"output_cost_per_token": 8e-06,
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@ -20433,8 +20431,6 @@
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@ -20508,8 +20504,6 @@
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@ -20581,8 +20575,6 @@
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@ -20624,8 +20616,6 @@
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@ -20647,8 +20637,6 @@
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@ -20937,8 +20925,6 @@
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@ -22037,6 +22021,8 @@
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@ -22351,6 +22349,8 @@
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@ -22396,6 +22396,8 @@
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@ -22442,6 +22444,8 @@
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@ -22485,6 +22489,8 @@
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@ -22528,6 +22534,8 @@
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@ -22566,8 +22574,6 @@
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@ -22974,8 +22980,6 @@
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"/v1/chat/completions",
"/v1/batch",
@ -23057,8 +23061,6 @@
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"mode": "chat",
"output_cost_per_token": 4e-07,
"output_cost_per_token_flex": 2e-07,

4
tests/batches_tests/test_batch_custom_pricing.py
View file

@ -159,12 +159,12 @@ def test_batch_cost_calculator_applies_data_residency_uplift(
base_prompt, base_completion = batch_cost_calculator(
usage=usage,
model="gpt-5",
model="gpt-5.4",
custom_llm_provider="openai",
)
regional_prompt, regional_completion = batch_cost_calculator(
usage=usage,
model="gpt-5",
model="gpt-5.4",
custom_llm_provider="openai",
data_residency=data_residency,
)

34
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -1499,19 +1499,20 @@ def _local_model_cost_map():
@pytest.mark.parametrize("data_residency", ["eu", "us"])
def test_data_residency_applies_uplift(data_residency, _local_model_cost_map):
"""gpt-5 should apply the regional processing uplift multiplier when
data_residency is set."""
"""gpt-5.4 should apply the regional processing uplift multiplier when
data_residency is set. gpt-5.4+ (released 2026-03-05) carry the 10% uplift;
gpt-5 and older models do not."""
from litellm.types.utils import Usage
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
)
regional = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
data_residency=data_residency,
@ -1526,6 +1527,23 @@ def test_data_residency_applies_uplift(data_residency, _local_model_cost_map):
assert regional[1] == pytest.approx(base[1] * 1.10, rel=1e-9)
@pytest.mark.parametrize("model", ["gpt-5", "gpt-5-mini", "gpt-5-nano", "gpt-5-pro", "gpt-4o", "gpt-4.1"])
def test_data_residency_no_uplift_for_pre_march_2026_models(model, _local_model_cost_map):
"""Models released before 2026-03-05 must not have the regional uplift."""
from litellm.types.utils import Usage
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(model=model, usage=usage, custom_llm_provider="openai")
regional = generic_cost_per_token(
model=model, usage=usage, custom_llm_provider="openai", data_residency="eu"
)
assert base == regional, (
f"{model} should not have a regional uplift, but cost changed with data_residency"
)
def test_data_residency_no_uplift_for_unmarked_model(_local_model_cost_map):
"""A model without a regional_processing_uplift_multiplier_* entry should
fall back to base pricing, not error."""
@ -1555,12 +1573,12 @@ def test_data_residency_none_no_uplift(_local_model_cost_map):
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
)
explicit_none = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
data_residency=None,
@ -1576,13 +1594,13 @@ def test_data_residency_composes_with_service_tier(_local_model_cost_map):
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
priority_base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
service_tier="priority",
)
priority_eu = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
service_tier="priority",