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Merge pull request #39827 from BerriAI/litellm_azure_gpt_6_astra

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feat(cost-map): add azure/gpt-6-astra and azure/us/gpt-6-astra Foundry pricing
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Mateo Wang 2026-09-04 18:48:51 -07:00 • committed by GitHub
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7 changed files with 325 additions and 4 deletions
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9
litellm/llms/azure/responses/transformation.py
View file

@ -6,6 +6,7 @@ from openai.types.responses import ResponseReasoningItem
from litellm._logging import verbose_logger
from litellm.litellm_core_utils.url_utils import encode_url_path_segment
from litellm.llms.azure.chat.gpt_5_transformation import AzureOpenAIGPT5Config
from litellm.llms.azure.common_utils import BaseAzureLLM
from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
from litellm.types.llms.openai import *
@ -29,6 +30,14 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
def custom_llm_provider(self) -> LlmProviders:
return LlmProviders.AZURE
@staticmethod
def _supports_reasoning_effort_none(model: str) -> bool:
return AzureOpenAIGPT5Config._supports_reasoning_effort_level(model, "none")
@staticmethod
def _effort_resolves_to_none(model: str, effort: str | None) -> bool:
return AzureOpenAIGPT5Config.effort_resolves_to_none(model, effort)
def get_supported_openai_params(self, model: str) -> list:
"""
Azure Responses API does not support context_management (compaction).

94
litellm/model_prices_and_context_window_backup.json
View file

@ -7157,6 +7157,53 @@
"supports_xhigh_reasoning_effort": true,
"supports_minimal_reasoning_effort": false
},
"azure/gpt-6-astra": {
"cache_creation_input_token_cost": 1.25e-05,
"cache_creation_input_token_cost_above_272k_tokens": 2.5e-05,
"cache_read_input_token_cost": 1e-06,
"cache_read_input_token_cost_above_272k_tokens": 2e-06,
"input_cost_per_token": 1e-05,
"input_cost_per_token_above_272k_tokens": 2e-05,
"litellm_provider": "azure",
"max_input_tokens": 922000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 5e-05,
"output_cost_per_token_above_272k_tokens": 7.5e-05,
"search_context_cost_per_query": {
"search_context_size_high": 0.01,
"search_context_size_low": 0.01,
"search_context_size_medium": 0.01
},
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_computer_use": true,
"supports_function_calling": true,
"supports_max_reasoning_effort": true,
"supports_minimal_reasoning_effort": false,
"supports_native_streaming": true,
"supports_none_reasoning_effort": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true,
"supports_web_search": true,
"supports_xhigh_reasoning_effort": true
},
"azure/us/gpt-5.6": {
"cache_creation_input_token_cost": 6.875e-06,
"cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,
@ -7376,6 +7423,53 @@
"supports_xhigh_reasoning_effort": true,
"supports_minimal_reasoning_effort": false
},
"azure/us/gpt-6-astra": {
"cache_creation_input_token_cost": 1.375e-05,
"cache_creation_input_token_cost_above_272k_tokens": 2.75e-05,
"cache_read_input_token_cost": 1.1e-06,
"cache_read_input_token_cost_above_272k_tokens": 2.2e-06,
"input_cost_per_token": 1.1e-05,
"input_cost_per_token_above_272k_tokens": 2.2e-05,
"litellm_provider": "azure",
"max_input_tokens": 922000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 5.5e-05,
"output_cost_per_token_above_272k_tokens": 8.25e-05,
"search_context_cost_per_query": {
"search_context_size_high": 0.01,
"search_context_size_low": 0.01,
"search_context_size_medium": 0.01
},
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_computer_use": true,
"supports_function_calling": true,
"supports_max_reasoning_effort": true,
"supports_minimal_reasoning_effort": false,
"supports_native_streaming": true,
"supports_none_reasoning_effort": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true,
"supports_web_search": true,
"supports_xhigh_reasoning_effort": true
},
"azure/eu/gpt-5.6": {
"cache_creation_input_token_cost": 6.875e-06,
"cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,

94
model_prices_and_context_window.json
View file

@ -7157,6 +7157,53 @@
"supports_xhigh_reasoning_effort": true,
"supports_minimal_reasoning_effort": false
},
"azure/gpt-6-astra": {
"cache_creation_input_token_cost": 1.25e-05,
"cache_creation_input_token_cost_above_272k_tokens": 2.5e-05,
"cache_read_input_token_cost": 1e-06,
"cache_read_input_token_cost_above_272k_tokens": 2e-06,
"input_cost_per_token": 1e-05,
"input_cost_per_token_above_272k_tokens": 2e-05,
"litellm_provider": "azure",
"max_input_tokens": 922000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 5e-05,
"output_cost_per_token_above_272k_tokens": 7.5e-05,
"search_context_cost_per_query": {
"search_context_size_high": 0.01,
"search_context_size_low": 0.01,
"search_context_size_medium": 0.01
},
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_computer_use": true,
"supports_function_calling": true,
"supports_max_reasoning_effort": true,
"supports_minimal_reasoning_effort": false,
"supports_native_streaming": true,
"supports_none_reasoning_effort": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true,
"supports_web_search": true,
"supports_xhigh_reasoning_effort": true
},
"azure/us/gpt-5.6": {
"cache_creation_input_token_cost": 6.875e-06,
"cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,
@ -7376,6 +7423,53 @@
"supports_xhigh_reasoning_effort": true,
"supports_minimal_reasoning_effort": false
},
"azure/us/gpt-6-astra": {
"cache_creation_input_token_cost": 1.375e-05,
"cache_creation_input_token_cost_above_272k_tokens": 2.75e-05,
"cache_read_input_token_cost": 1.1e-06,
"cache_read_input_token_cost_above_272k_tokens": 2.2e-06,
"input_cost_per_token": 1.1e-05,
"input_cost_per_token_above_272k_tokens": 2.2e-05,
"litellm_provider": "azure",
"max_input_tokens": 922000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 5.5e-05,
"output_cost_per_token_above_272k_tokens": 8.25e-05,
"search_context_cost_per_query": {
"search_context_size_high": 0.01,
"search_context_size_low": 0.01,
"search_context_size_medium": 0.01
},
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_computer_use": true,
"supports_function_calling": true,
"supports_max_reasoning_effort": true,
"supports_minimal_reasoning_effort": false,
"supports_native_streaming": true,
"supports_none_reasoning_effort": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true,
"supports_web_search": true,
"supports_xhigh_reasoning_effort": true
},
"azure/eu/gpt-5.6": {
"cache_creation_input_token_cost": 6.875e-06,
"cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,

43
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -2008,6 +2008,49 @@ def test_generic_cost_per_token_azure_gpt56(_local_model_cost_map,
assert round(completion_cost, 10) == round(output_cost * completion_tokens, 10)
@pytest.mark.parametrize("model,zone_multiplier", [("azure/gpt-6-astra", 1.0), ("azure/us/gpt-6-astra", 1.1)])
@pytest.mark.parametrize(
"prompt_tokens,input_side_multiplier,output_multiplier",
[(100000, 1.0, 1.0), (300000, 2.0, 1.5)],
)
def test_generic_cost_per_token_azure_gpt_6_astra_foundry_price_sheet(
_local_model_cost_map,
model,
zone_multiplier,
prompt_tokens,
input_side_multiplier,
output_multiplier,
):
"""Microsoft Foundry sells gpt-6-astra at the OpenAI rates: $10 input, $1 cache read, $12.50 cache write,
$50 output per 1M tokens on Standard Global, with the input side doubling and output 1.5x above 272K
prompt tokens. Standard US Data Zone carries the usual 10% uplift on every rate.
"""
cached_tokens = 50000
cache_write_tokens = 40000
text_tokens = prompt_tokens - cached_tokens - cache_write_tokens
completion_tokens = 1000
usage = Usage(
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
total_tokens=prompt_tokens + completion_tokens,
prompt_tokens_details=PromptTokensDetailsWrapper(
cached_tokens=cached_tokens, cache_write_tokens=cache_write_tokens
),
)
prompt_cost, completion_cost = generic_cost_per_token(
model=model,
usage=usage,
custom_llm_provider="azure",
)
input_side = zone_multiplier * input_side_multiplier
assert prompt_cost == pytest.approx(
input_side * (text_tokens * 1e-5 + cached_tokens * 1e-6 + cache_write_tokens * 1.25e-5)
)
assert completion_cost == pytest.approx(zone_multiplier * output_multiplier * completion_tokens * 5e-5)
@pytest.mark.parametrize(
"model,expected_none,expected_xhigh,expected_minimal",
[

28
tests/test_litellm/llms/azure/chat/test_azure_gpt5_transformation.py
View file

@ -348,3 +348,31 @@ def test_azure_gpt_6_astra_takes_the_reasoning_series_request_shape():
assert params["max_completion_tokens"] == 100
assert "max_tokens" not in params
assert params["reasoning_effort"] == "max"
@pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
def test_azure_gpt6_astra_reasoning_effort_none_unlocks_temperature(config: AzureOpenAIGPT5Config, model: str):
"""Foundry's gpt-6-astra accepts reasoning_effort='none' and, only then, a non-default
temperature (verified live against a Foundry deployment), unlike OpenAI's gpt-6-astra."""
params = config.map_openai_params(
non_default_params={"temperature": 0.2, "reasoning_effort": "none"},
optional_params={},
model=model,
drop_params=False,
api_version="2025-04-01-preview",
)
assert params["temperature"] == 0.2
assert params["reasoning_effort"] == "none"
@pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
def test_azure_gpt6_astra_rejects_reasoning_effort_minimal(config: AzureOpenAIGPT5Config, model: str):
"""Foundry's gpt-6-astra lists none, low, medium, high, xhigh and max but not minimal."""
with pytest.raises(litellm.utils.UnsupportedParamsError):
config.map_openai_params(
non_default_params={"reasoning_effort": "minimal"},
optional_params={},
model=model,
drop_params=False,
api_version="2025-04-01-preview",
)

43
tests/test_litellm/llms/azure/response/test_azure_transformation.py
View file

@ -1,11 +1,10 @@
from copy import deepcopy
from unittest.mock import patch
from unittest.mock import MagicMock, patch
import pytest
from unittest.mock import MagicMock
import litellm
from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
from litellm.llms.azure.responses.o_series_transformation import (
AzureOpenAIOSeriesResponsesAPIConfig,
)
@ -613,3 +612,39 @@ class TestAzureResponsesAPIConfig:
assert result["tools"][0] is tool
assert "anyOf" in result["tools"][0]["parameters"]
@pytest.fixture()
def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> None:
"""Pin the bundled cost map: the published map lags a key added in this repo."""
monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
monkeypatch.setattr(litellm, "model_cost", get_model_cost_map(url=litellm.model_cost_map_url))
litellm.add_known_models(model_cost_map=litellm.model_cost)
def test_azure_responses_gpt6_astra_reasoning_effort_none_unlocks_temperature(local_model_cost_map: None):
"""Foundry's gpt-6-astra accepts reasoning.effort='none' with a non-default temperature
while OpenAI's gpt-6-astra does not, so the gate must read the azure/ cost-map entry
for the bare deployment name rather than OpenAI's."""
params = AzureOpenAIResponsesAPIConfig().map_openai_params(
response_api_optional_params=ResponsesAPIOptionalRequestParams(
temperature=0.2,
reasoning={"effort": "none"},
),
model="gpt-6-astra",
drop_params=False,
)
assert params["temperature"] == 0.2
assert params["reasoning"] == {"effort": "none"}
def test_azure_responses_gpt6_astra_rejects_temperature_while_reasoning(local_model_cost_map: None):
with pytest.raises(litellm.UnsupportedParamsError):
AzureOpenAIResponsesAPIConfig().map_openai_params(
response_api_optional_params=ResponsesAPIOptionalRequestParams(
temperature=0.2,
reasoning={"effort": "low"},
),
model="gpt-6-astra",
drop_params=False,
)

18
tests/test_litellm/router_utils/test_reasoning_effort_capability.py
View file

@ -388,3 +388,21 @@ class TestGpt6AstraAdvertisesItsDocumentedLevels:
"xhigh",
"max",
)
@pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
def test_a_foundry_deployment_also_advertises_none(self, local_model_cost_map, model):
"""Microsoft Foundry serves the same model but its API accepts reasoning_effort none
(verified live: 200 with zero reasoning tokens, and it unlocks temperature), which
OpenAI's rejects, so an Azure deployment offers none on top of low through max."""
from litellm.utils import _get_model_info_helper
model_info = dict(_get_model_info_helper(model=model, custom_llm_provider="azure"))
assert resolve_supported_reasoning_efforts(model_info, deployment_is_mapped=True) == (
"none",
"low",
"medium",
"high",
"xhigh",
"max",
)