fix(cost): add the gpt-5.5-pro batch long-context tier and ignore malformed batch tier keys

basedpyright-code-budget.json

@@ -3,7 +3,7 @@
     "limit": 13429
   },
   "reportArgumentType": {
-    "limit": 2198
+    "limit": 1913
   },
   "reportAssignmentType": {
     "limit": 319

litellm/cost_calculator.py

@@ -27,11 +27,11 @@ from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import
 from litellm.litellm_core_utils.llm_cost_calc.utils import (
     CostCalculatorUtils,
     _generic_cost_per_character,
-    _get_batch_cost_rates,
     _get_regional_uplift_multiplier,
     _get_service_tier_cost_key,
     calculate_cost_component,
     generic_cost_per_token,
+    get_batch_cost_rates,
     get_billable_input_tokens,
     get_token_type_cost_breakdown,
     parse_prompt_tokens_details,
@@ -2242,7 +2242,7 @@ def batch_cost_calculator(
     if not model_info:
         return 0.0, 0.0
 
-    input_cost_per_token_batches, output_cost_per_token_batches = _get_batch_cost_rates(
+    input_cost_per_token_batches, output_cost_per_token_batches = get_batch_cost_rates(
         model_info, usage, custom_llm_provider
     )
     input_cost_per_token: Final = model_info.get("input_cost_per_token")

litellm/litellm_core_utils/llm_cost_calc/utils.py

@@ -62,6 +62,7 @@ _SERVICE_TIER_TO_COST_KEY_SUFFIX: Final[Mapping[str, str]] = MappingProxyType(
 
 _INCLUSIVE_THRESHOLD_PROVIDERS: Final = frozenset({"xai"})
 _BATCH_KEY_SUFFIX: Final = "_batches"
+_BATCH_TIER_INPUT_KEY: Final = re.compile(r"^input_cost_per_token_above_\d+k?_tokens_batches$")
 _NON_STANDARD_THRESHOLD_SUFFIXES: Final = (*_SERVICE_TIER_SUFFIXES, _BATCH_KEY_SUFFIX)
 
 
@@ -252,14 +253,12 @@ def _batch_rate(model_info: ModelInfo, key: str) -> float | None:
     return value if isinstance(value, (int, float)) else None
 
 
-def _get_batch_cost_rates(
+def get_batch_cost_rates(
     model_info: ModelInfo, usage: Usage, custom_llm_provider: str | None
 ) -> tuple[float | None, float | None]:
     inclusive: Final = _uses_inclusive_token_thresholds(custom_llm_provider)
     tier_input_keys: Final = tuple(
-        key
-        for key, value in model_info.items()
-        if key.startswith("input_cost_per_token_above_") and key.endswith(_BATCH_KEY_SUFFIX) and value is not None
+        key for key, value in model_info.items() if _BATCH_TIER_INPUT_KEY.match(key) and value is not None
     )
     crossed_input_key: Final = next(
         (

litellm/model_prices_and_context_window_backup.json

@@ -30839,6 +30839,7 @@
         "input_cost_per_token_above_272k_tokens": 6e-05,
         "input_cost_per_token_flex": 1.5e-05,
         "input_cost_per_token_batches": 1.5e-05,
+        "input_cost_per_token_above_272k_tokens_batches": 3e-05,
         "litellm_provider": "openai",
         "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
@@ -30848,6 +30849,7 @@
         "output_cost_per_token_above_272k_tokens": 0.00027,
         "output_cost_per_token_flex": 9e-05,
         "output_cost_per_token_batches": 9e-05,
+        "output_cost_per_token_above_272k_tokens_batches": 0.000135,
         "regional_processing_uplift_multiplier_eu": 1.1,
         "regional_processing_uplift_multiplier_us": 1.1,
         "search_context_cost_per_query": {
@@ -30889,6 +30891,7 @@
         "input_cost_per_token_above_272k_tokens": 6e-05,
         "input_cost_per_token_flex": 1.5e-05,
         "input_cost_per_token_batches": 1.5e-05,
+        "input_cost_per_token_above_272k_tokens_batches": 3e-05,
         "litellm_provider": "openai",
         "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
@@ -30898,6 +30901,7 @@
         "output_cost_per_token_above_272k_tokens": 0.00027,
         "output_cost_per_token_flex": 9e-05,
         "output_cost_per_token_batches": 9e-05,
+        "output_cost_per_token_above_272k_tokens_batches": 0.000135,
         "regional_processing_uplift_multiplier_eu": 1.1,
         "regional_processing_uplift_multiplier_us": 1.1,
         "search_context_cost_per_query": {

model_prices_and_context_window.json

@@ -30839,6 +30839,7 @@
         "input_cost_per_token_above_272k_tokens": 6e-05,
         "input_cost_per_token_flex": 1.5e-05,
         "input_cost_per_token_batches": 1.5e-05,
+        "input_cost_per_token_above_272k_tokens_batches": 3e-05,
         "litellm_provider": "openai",
         "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
@@ -30848,6 +30849,7 @@
         "output_cost_per_token_above_272k_tokens": 0.00027,
         "output_cost_per_token_flex": 9e-05,
         "output_cost_per_token_batches": 9e-05,
+        "output_cost_per_token_above_272k_tokens_batches": 0.000135,
         "regional_processing_uplift_multiplier_eu": 1.1,
         "regional_processing_uplift_multiplier_us": 1.1,
         "search_context_cost_per_query": {
@@ -30889,6 +30891,7 @@
         "input_cost_per_token_above_272k_tokens": 6e-05,
         "input_cost_per_token_flex": 1.5e-05,
         "input_cost_per_token_batches": 1.5e-05,
+        "input_cost_per_token_above_272k_tokens_batches": 3e-05,
         "litellm_provider": "openai",
         "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
@@ -30898,6 +30901,7 @@
         "output_cost_per_token_above_272k_tokens": 0.00027,
         "output_cost_per_token_flex": 9e-05,
         "output_cost_per_token_batches": 9e-05,
+        "output_cost_per_token_above_272k_tokens_batches": 0.000135,
         "regional_processing_uplift_multiplier_eu": 1.1,
         "regional_processing_uplift_multiplier_us": 1.1,
         "search_context_cost_per_query": {

tests/test_litellm/test_cost_calculator.py

@@ -1,6 +1,7 @@
 
 import json
 from pathlib import Path
+from typing import cast
 
 import pytest
 
@@ -4546,3 +4547,50 @@ def test_regular_path_never_bills_the_batch_tier_keys(_local_model_cost_map, mon
 
     assert prompt_cost == pytest.approx(300_035 * 2e-6)
     assert completion_cost == pytest.approx(64 * 8e-6)
+
+
+def _lacks_half_price_batch_tier(entry: dict) -> bool:
+    return any(
+        entry.get(f"{side}_cost_per_token_above_272k_tokens_batches")
+        != entry[f"{side}_cost_per_token_above_272k_tokens"] / 2
+        for side in ("input", "output")
+    )
+
+
+def test_every_openai_entry_with_long_context_and_batch_rates_carries_the_batch_tier(_local_model_cost_map):
+    offenders = [
+        name
+        for name, entry in litellm.model_cost.items()
+        if isinstance(entry, dict)
+        and entry.get("litellm_provider") == "openai"
+        and entry.get("input_cost_per_token_above_272k_tokens") is not None
+        and entry.get("input_cost_per_token_batches") is not None
+        and _lacks_half_price_batch_tier(entry)
+    ]
+
+    assert offenders == []
+
+
+def test_batch_cost_calculator_ignores_malformed_batch_tier_keys():
+    from litellm.cost_calculator import batch_cost_calculator
+
+    usage = Usage(prompt_tokens=300_035, completion_tokens=64, total_tokens=300_099)
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 2e-6,
+            "output_cost_per_token": 8e-6,
+            "input_cost_per_token_batches": 1e-6,
+            "output_cost_per_token_batches": 4e-6,
+            "input_cost_per_token_above_272k_tokens_batches": 2e-6,
+            "output_cost_per_token_above_272k_tokens_batches": 6e-6,
+            "input_cost_per_token_above_lots_tokens_batches": 1.0,
+        },
+    )
+
+    prompt_cost, completion_cost = batch_cost_calculator(
+        usage=usage, model="gpt-5.4", custom_llm_provider="openai", model_info=model_info
+    )
+
+    assert prompt_cost == pytest.approx(300_035 * 2e-6)
+    assert completion_cost == pytest.approx(64 * 6e-6)