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Merge pull request #40740 from BerriAI/litellm_bedrock_openai_xhigh_flags

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fix(cost-map): bedrock reasoning effort flags, registry audit fixes for vertex/openai/together/openrouter, absorb cerebras and inception rows
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Mateo Wang 2026-09-11 14:41:18 -07:00 • committed by GitHub
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litellm/model_prices_and_context_window_backup.json
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@ -13118,6 +13118,22 @@
"supports_reasoning": true,
"supports_tool_choice": true
},
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"max_tokens": 32768,
"mode": "chat",
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"source": "https://api.cerebras.ai/public/v1/models/qwen-3.8-27b",
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},
"chatdolphin": {
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"litellm_provider": "nlp_cloud",
@ -31328,8 +31344,6 @@
"cache_read_input_token_cost_above_272k_tokens_flex": 5e-07
},
"gpt-5.5-pro": {
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"input_cost_per_token_above_272k_tokens": 6e-05,
"input_cost_per_token_flex": 1.5e-05,
@ -31378,8 +31392,6 @@
"supports_low_reasoning_effort": false
},
"gpt-5.5-pro-2026-04-23": {
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@ -31532,8 +31544,6 @@
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},
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@ -31583,8 +31593,6 @@
"output_cost_per_token_above_272k_tokens_flex": 0.000135
},
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@ -33891,6 +33899,20 @@
"supports_system_messages": true,
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},
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@ -39127,19 +39149,21 @@
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},
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@ -39202,36 +39226,56 @@
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},
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},
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"source": "https://openrouter.ai/deepseek/deepseek-v4-pro-0813",
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},
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@ -40010,6 +40054,28 @@
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},
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},
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@ -40138,13 +40204,13 @@
"supports_tool_choice": true
},
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@ -40177,7 +40243,7 @@
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@ -40188,7 +40254,8 @@
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@ -40205,13 +40272,13 @@
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@ -40298,18 +40365,19 @@
"supports_web_search": true
},
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},
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@ -43134,7 +43202,11 @@
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"source": "https://api.together.xyz/v1/models"
},
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@ -43142,7 +43214,11 @@
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},
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@ -43354,7 +43430,11 @@
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@ -43362,7 +43442,11 @@
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@ -48093,27 +48177,29 @@
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},
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},
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@ -48163,15 +48249,16 @@
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@ -55273,11 +55360,14 @@
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@ -55312,11 +55402,14 @@
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@ -55341,10 +55434,12 @@
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@ -55373,10 +55468,12 @@
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@ -55441,8 +55541,11 @@
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@ -55467,8 +55570,11 @@
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@ -55493,8 +55599,11 @@
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@ -55519,8 +55628,11 @@
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@ -55545,8 +55657,11 @@
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@ -55571,8 +55686,11 @@
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@ -55602,10 +55720,14 @@
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@ -55631,9 +55753,13 @@
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@ -55659,9 +55785,13 @@
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@ -55694,11 +55824,13 @@
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@ -55730,11 +55862,13 @@
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476
model_prices_and_context_window.json
View file

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"supports_prompt_caching": true
},
"openrouter/openai/gpt-5.6-luna-pro": {
"input_cost_per_token": 2e-07,
"output_cost_per_token": 1.2e-06,
"cache_read_input_token_cost": 2e-08,
"cache_creation_input_token_cost": 2.5e-07,
"input_cost_per_token_above_272k_tokens": 4e-07,
"output_cost_per_token_above_272k_tokens": 1.8e-06,
"cache_read_input_token_cost_above_272k_tokens": 4e-08,
"litellm_provider": "openrouter",
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"source": "https://openrouter.ai/openai/gpt-5.6-luna-pro",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_vision": true,
"supports_pdf_input": true,
"supports_prompt_caching": true
},
"openrouter/openai/gpt-5.6-terra": {
"input_cost_per_token": 2e-06,
"output_cost_per_token": 1.2e-05,
@ -62327,6 +62598,28 @@
"cache_read_input_token_cost": 2e-07,
"supports_prompt_caching": true
},
"openrouter/openai/gpt-5.6-terra-pro": {
"input_cost_per_token": 2e-06,
"output_cost_per_token": 1.2e-05,
"cache_read_input_token_cost": 2e-07,
"cache_creation_input_token_cost": 2.5e-06,
"input_cost_per_token_above_272k_tokens": 4e-06,
"output_cost_per_token_above_272k_tokens": 1.8e-05,
"cache_read_input_token_cost_above_272k_tokens": 4e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"source": "https://openrouter.ai/openai/gpt-5.6-terra-pro",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_vision": true,
"supports_pdf_input": true,
"supports_prompt_caching": true
},
"openrouter/openai/o3": {
"input_cost_per_token": 2e-06,
"output_cost_per_token": 8e-06,
@ -62560,6 +62853,28 @@
"supports_pdf_input": true,
"supports_prompt_caching": true
},
"openrouter/openai/gpt-6-astra-pro": {
"input_cost_per_token": 1e-05,
"output_cost_per_token": 5e-05,
"cache_read_input_token_cost": 1e-06,
"cache_creation_input_token_cost": 1.25e-05,
"input_cost_per_token_above_272k_tokens": 2e-05,
"output_cost_per_token_above_272k_tokens": 7.5e-05,
"cache_read_input_token_cost_above_272k_tokens": 2e-06,
"litellm_provider": "openrouter",
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"source": "https://openrouter.ai/openai/gpt-6-astra-pro",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_vision": true,
"supports_pdf_input": true,
"supports_prompt_caching": true
},
"openrouter/qwen/qwen3.8-flash": {
"input_cost_per_token": 1.5e-07,
"output_cost_per_token": 4.7e-07,
@ -62579,9 +62894,9 @@
"supports_prompt_caching": true
},
"openrouter/z-ai/glm-5.3-flash": {
"input_cost_per_token": 7.5e-08,
"output_cost_per_token": 2.5e-07,
"cache_read_input_token_cost": 1.5e-08,
"input_cost_per_token": 1.5e-07,
"output_cost_per_token": 5e-07,
"cache_read_input_token_cost": 3e-08,
"litellm_provider": "openrouter",
"max_input_tokens": 1310720,
"max_output_tokens": 131072,
@ -62696,6 +63011,25 @@
"supports_vision": true,
"supports_prompt_caching": true
},
"openrouter/qwen/qwen3.8-max-0902": {
"input_cost_per_token": 2e-06,
"output_cost_per_token": 6e-06,
"cache_read_input_token_cost": 2.5e-07,
"cache_creation_input_token_cost": 2.5e-06,
"litellm_provider": "openrouter",
"max_input_tokens": 1000000,
"max_output_tokens": 131072,
"max_tokens": 131072,
"mode": "chat",
"source": "https://openrouter.ai/qwen/qwen3.8-max-0902",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_vision": true,
"supports_pdf_input": false,
"supports_prompt_caching": true
},
"openrouter/deepseek/deepseek-v4-flash-0731": {
"input_cost_per_token": 6.5e-08,
"output_cost_per_token": 1.8e-07,
@ -62767,9 +63101,9 @@
"supports_vision": false
},
"openrouter/moonshotai/kimi-k3": {
"input_cost_per_token": 3e-06,
"output_cost_per_token": 1.5e-05,
"cache_read_input_token_cost": 3e-07,
"input_cost_per_token": 2.1e-06,
"output_cost_per_token": 1.053e-05,
"cache_read_input_token_cost": 2.35e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 1048576,
"max_output_tokens": 943718,
@ -62866,9 +63200,9 @@
"supports_prompt_caching": true
},
"openrouter/z-ai/glm-5.2": {
"input_cost_per_token": 9.66e-07,
"output_cost_per_token": 3.036e-06,
"cache_read_input_token_cost": 1.932e-07,
"input_cost_per_token": 6e-07,
"output_cost_per_token": 2e-06,
"cache_read_input_token_cost": 1.5e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 1048576,
"max_output_tokens": 131072,
@ -62899,9 +63233,9 @@
"supports_vision": false
},
"openrouter/moonshotai/kimi-k2.7-code": {
"input_cost_per_token": 6.6e-07,
"output_cost_per_token": 3.4e-06,
"cache_read_input_token_cost": 1.8e-07,
"input_cost_per_token": 7.1e-07,
"output_cost_per_token": 3.5e-06,
"cache_read_input_token_cost": 1.5e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 262144,
"max_output_tokens": 235929,
@ -63149,10 +63483,28 @@
"supports_vision": true,
"supports_pdf_input": true
},
"openrouter/openai/gpt-chat-latest": {
"input_cost_per_token": 5e-06,
"output_cost_per_token": 3e-05,
"cache_read_input_token_cost": 5e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 400000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"source": "https://openrouter.ai/openai/gpt-chat-latest",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": false,
"supports_response_schema": true,
"supports_vision": true,
"supports_pdf_input": true,
"supports_prompt_caching": true
},
"openrouter/deepseek/deepseek-v4-flash": {
"input_cost_per_token": 8.778e-08,
"output_cost_per_token": 1.7556e-07,
"cache_read_input_token_cost": 1.7556e-08,
"input_cost_per_token": 8.54e-08,
"output_cost_per_token": 1.708e-07,
"cache_read_input_token_cost": 1.708e-08,
"litellm_provider": "openrouter",
"max_input_tokens": 1048576,
"max_output_tokens": 384000,
@ -63185,8 +63537,8 @@
"supports_prompt_caching": true
},
"openrouter/google/gemma-4-26b-a4b-it": {
"input_cost_per_token": 7e-08,
"output_cost_per_token": 3.4e-07,
"input_cost_per_token": 4.2e-08,
"output_cost_per_token": 2.2e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 262144,
"max_output_tokens": 16384,
@ -63868,7 +64220,7 @@
"supports_vision": false
},
"openrouter/qwen/qwen3-next-80b-a3b-instruct": {
"input_cost_per_token": 1e-07,
"input_cost_per_token": 9e-08,
"output_cost_per_token": 1.1e-06,
"cache_read_input_token_cost": 7e-08,
"litellm_provider": "openrouter",
@ -63994,8 +64346,8 @@
"supports_vision": false
},
"openrouter/qwen/qwen3-30b-a3b-instruct-2507": {
"input_cost_per_token": 4.815e-08,
"output_cost_per_token": 1.9305e-07,
"input_cost_per_token": 9e-08,
"output_cost_per_token": 3e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 262144,
"max_output_tokens": 32000,
@ -64193,8 +64545,8 @@
"supports_vision": false
},
"openrouter/qwen/qwen3-14b": {
"input_cost_per_token": 1.2e-07,
"output_cost_per_token": 2.4e-07,
"input_cost_per_token": 2.275e-07,
"output_cost_per_token": 9.1e-07,
"litellm_provider": "openrouter",
"max_input_tokens": 131072,
"max_output_tokens": 16384,

4
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -1715,7 +1715,7 @@ def test_generic_cost_per_token_gpt55(_local_model_cost_map):
def test_generic_cost_per_token_gpt55_pro(_local_model_cost_map):
"""gpt-5.5-pro: responses-only model — $30/1M input, $180/1M output, $3/1M cached input."""
"""gpt-5.5-pro: responses-only model, $30/1M input, $180/1M output, no cached input rate published."""
model = "gpt-5.5-pro"
custom_llm_provider = "openai"
@ -1724,7 +1724,7 @@ def test_generic_cost_per_token_gpt55_pro(_local_model_cost_map):
# Sanity-check the map values match OpenAI's published pricing.
assert model_cost_map["input_cost_per_token"] == 3e-5
assert model_cost_map["output_cost_per_token"] == 1.8e-4
assert model_cost_map["cache_read_input_token_cost"] == 3e-6
assert "cache_read_input_token_cost" not in model_cost_map
assert model_cost_map["litellm_provider"] == "openai"
# gpt-5.5-pro is a responses-only model (no /v1/chat/completions endpoint).
assert model_cost_map["mode"] == "responses"

23
tests/test_litellm/llms/cerebras/test_cerebras_chat_transformation.py
View file

@ -1,3 +1,6 @@
import pytest
import litellm
from litellm.llms.cerebras.chat import CerebrasConfig
@ -59,3 +62,23 @@ def test_map_openai_params_preserves_max_retries_zero_falsy() -> None:
assert "max_retries" in result and result["max_retries"] == 0, (
f"max_retries=0 (falsy) must not be silently omitted; got: {result!r}"
)
def test_qwen_3_8_27b_cost_and_tokens(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
model = "cerebras/qwen-3.8-27b"
prompt_cost, completion_cost = litellm.cost_per_token(
model=model,
prompt_tokens=1000,
completion_tokens=1000,
)
assert abs(prompt_cost - 0.00099) < 1e-9
assert abs(completion_cost - 0.00149) < 1e-9
model_info = litellm.get_model_info(model)
assert model_info["max_input_tokens"] == 65536
assert model_info["max_output_tokens"] == 32768
assert model_info["supports_vision"] is True
assert model_info["supports_reasoning"] is True
assert model_info["supports_parallel_function_calling"] is True

23
tests/test_litellm/llms/inception/test_inception_chat_transformation.py
View file

@ -7,6 +7,7 @@ import os
from unittest import mock
import httpx
import pytest
import litellm
from litellm.llms.inception.chat.transformation import InceptionChatConfig
@ -238,6 +239,7 @@ def test_inception_model_list_populated(monkeypatch):
litellm.add_known_models()
assert "inception/mercury-2" in litellm.inception_models
assert "inception/mercury-2.5" in litellm.inception_models
for model in litellm.inception_models:
assert model.startswith("inception/")
@ -304,3 +306,24 @@ def test_inception_completion_targets_inception_endpoint():
assert captured["body"]["model"] == "mercury-2"
assert captured["body"]["tool_choice"] == "auto"
assert response.choices[0].message.content == "hi"
def test_inception_mercury_2_5_cost_and_tokens(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
model = "inception/mercury-2.5"
prompt_cost, completion_cost = litellm.cost_per_token(
model=model,
prompt_tokens=1000,
completion_tokens=500,
)
assert abs(prompt_cost - 0.0002) < 1e-9
assert abs(completion_cost - 0.000375) < 1e-9
model_info = litellm.get_model_info(model)
assert model_info["max_input_tokens"] == 260000
assert model_info["max_output_tokens"] == 65536
assert model_info["litellm_provider"] == "inception"
assert model_info["mode"] == "chat"
assert model_info["supports_function_calling"] is True
assert model_info["supports_response_schema"] is True

49
tests/test_litellm/test_model_prices_schema.py
View file

@ -4,6 +4,8 @@ import importlib.util
import json
import re
from pathlib import Path
from types import MappingProxyType
from typing import Final
import jsonschema
import pytest
@ -217,3 +219,50 @@ def test_chat_latest_declares_the_one_effort_openai_accepts(prices: dict):
with no declared levels resolves to None, which lets /model_group/info and the dashboard offer
levels the upstream will 400 on."""
assert resolve_supported_reasoning_efforts(prices["chat-latest"], deployment_is_mapped=True) == ("medium",)
BEDROCK_OPENAI_GPT_MARKERS: Final = ("openai.gpt-5.4", "openai.gpt-5.5", "openai.gpt-5.6", "openai.gpt-6-astra")
BEDROCK_PROVIDERS: Final = frozenset(("bedrock", "bedrock_converse", "bedrock_mantle"))
BEDROCK_ROW_PREFIXES: Final = ("bedrock_mantle/", "us.", "global.")
GPT_5_4_BEDROCK_LADDER: Final = ("none", "low", "medium", "high", "xhigh")
GPT_5_6_BEDROCK_LADDER: Final = ("none", "low", "medium", "high", "xhigh", "max")
GPT_6_ASTRA_BEDROCK_LADDER: Final = ("low", "medium", "high", "xhigh", "max")
BEDROCK_OPENAI_GPT_LADDERS: Final = MappingProxyType(
{
"bedrock_mantle/openai.gpt-5.4": GPT_5_4_BEDROCK_LADDER,
"bedrock_mantle/openai.gpt-5.5": GPT_5_4_BEDROCK_LADDER,
**{
f"{prefix}openai.gpt-5.6-{variant}": GPT_5_6_BEDROCK_LADDER
for prefix in BEDROCK_ROW_PREFIXES
for variant in ("luna", "sol", "terra")
},
**{f"{prefix}openai.gpt-6-astra": GPT_6_ASTRA_BEDROCK_LADDER for prefix in BEDROCK_ROW_PREFIXES},
}
)
@pytest.mark.parametrize(
("name", "ladder"), tuple(BEDROCK_OPENAI_GPT_LADDERS.items()), ids=tuple(BEDROCK_OPENAI_GPT_LADDERS)
)
def test_bedrock_openai_gpt_rows_advertise_the_ladder_bedrock_accepts(prices: dict, name: str, ladder: tuple[str, ...]):
"""Each ladder is the set of levels Bedrock answered 200 to for that row through the proxy on
2026-09-11 (PR #40740): the Mantle rows go out over its Responses endpoint and the Converse rows
over inference profiles. Bedrock differs from the direct OpenAI rows in two places, gpt-5.6 and
gpt-6-astra take max there, and gpt-6-astra refuses none; minimal is refused on every row.
xhigh and max are opt-in for the resolver, so a row missing either flag silently drops that
level from every group it belongs to."""
assert resolve_supported_reasoning_efforts(prices[name], deployment_is_mapped=True) == ladder
def test_every_bedrock_openai_gpt_row_advertises_xhigh(prices: dict):
"""The GovCloud and gpt-5.6-cyber rows cannot be called from our account, so they carry the
family's xhigh flag rather than a measured ladder."""
missing: Final = [
name
for name, entry in prices.items()
if isinstance(entry, dict)
and entry.get("litellm_provider") in BEDROCK_PROVIDERS
and any(marker in name for marker in BEDROCK_OPENAI_GPT_MARKERS)
and "xhigh" not in (resolve_supported_reasoning_efforts(entry, deployment_is_mapped=True) or ())
]
assert missing == []