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Add Azure AI DeepSeek V4 Pro metadata

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Emerson Gomes 2026-05-19 13:19:34 -03:00
parent a72414a061
commit 4a7df29b67
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3 changed files with 105 additions and 11 deletions
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19
litellm/model_prices_and_context_window_backup.json
View file

@ -7093,6 +7093,25 @@
"supports_function_calling": true,
"supports_tool_choice": true
},
"azure_ai/deepseek-v4-pro": {
"input_cost_per_token": 1.74e-06,
"litellm_provider": "azure_ai",
"max_input_tokens": 1000000,
"max_output_tokens": 1000000,
"max_tokens": 1000000,
"mode": "chat",
"output_cost_per_token": 3.48e-06,
"source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-deepseek-v4-flash-and-v4-pro-in-microsoft-foundry/4515174",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_reasoning": true,
"supports_tool_choice": true
},
"azure_ai/embed-v-4-0": {
"input_cost_per_token": 1.2e-07,
"litellm_provider": "azure_ai",

19
model_prices_and_context_window.json
View file

@ -7122,6 +7122,25 @@
"supports_function_calling": true,
"supports_tool_choice": true
},
"azure_ai/deepseek-v4-pro": {
"input_cost_per_token": 1.74e-06,
"litellm_provider": "azure_ai",
"max_input_tokens": 1000000,
"max_output_tokens": 1000000,
"max_tokens": 1000000,
"mode": "chat",
"output_cost_per_token": 3.48e-06,
"source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-deepseek-v4-flash-and-v4-pro-in-microsoft-foundry/4515174",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_reasoning": true,
"supports_tool_choice": true
},
"azure_ai/embed-v-4-0": {
"input_cost_per_token": 1.2e-07,
"litellm_provider": "azure_ai",

78
tests/test_litellm/llms/azure_ai/test_azure_ai_cost_calculator.py
View file

@ -2,15 +2,22 @@
Test Azure AI cost calculator, especially Model Router flat cost.
"""
import os
import pytest
import litellm
from litellm.llms.azure_ai.cost_calculator import (
_is_azure_model_router,
cost_per_token,
)
from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
from litellm.types.utils import Usage
from litellm.utils import get_model_info
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = get_model_cost_map(url="")
# Get the flat cost from model_prices_and_context_window.json
_model_info = get_model_info(model="model_router", custom_llm_provider="azure_ai")
AZURE_MODEL_ROUTER_FLAT_COST_PER_M_INPUT_TOKENS = (
@ -459,18 +466,21 @@ class TestAzureAIServiceTierCostCalculation:
@pytest.fixture(autouse=True)
def register_test_model(self):
import litellm
litellm.register_model(model_cost={
"test-azure-ai-model": {
"input_cost_per_token": 0.001,
"output_cost_per_token": 0.002,
"input_cost_per_token_priority": 0.01,
"output_cost_per_token_priority": 0.02,
"input_cost_per_token_flex": 0.0005,
"output_cost_per_token_flex": 0.001,
"litellm_provider": "azure_ai",
"max_tokens": 8192,
litellm.register_model(
model_cost={
"test-azure-ai-model": {
"input_cost_per_token": 0.001,
"output_cost_per_token": 0.002,
"input_cost_per_token_priority": 0.01,
"output_cost_per_token_priority": 0.02,
"input_cost_per_token_flex": 0.0005,
"output_cost_per_token_flex": 0.001,
"litellm_provider": "azure_ai",
"max_tokens": 8192,
}
}
})
)
def test_service_tier_priority_higher_cost(self):
"""Priority tier should cost more than standard for azure_ai."""
@ -499,3 +509,49 @@ class TestAzureAIServiceTierCostCalculation:
assert flex_prompt < standard_prompt
assert flex_completion < standard_completion
@pytest.mark.parametrize(
"model_name",
["azure_ai/deepseek-v4-pro"],
)
def test_azure_ai_deepseek_v4_pro_model_info(model_name: str):
model_info = get_model_info(model=model_name)
assert model_info["litellm_provider"] == "azure_ai"
assert model_info["mode"] == "chat"
assert model_info["max_input_tokens"] == 1_000_000
assert model_info["max_output_tokens"] == 1_000_000
assert model_info["max_tokens"] == 1_000_000
assert model_info["input_cost_per_token"] == pytest.approx(1.74e-06)
assert model_info["output_cost_per_token"] == pytest.approx(3.48e-06)
assert model_info["supports_function_calling"] is True
assert model_info["supports_reasoning"] is True
assert model_info["supports_tool_choice"] is True
def test_azure_ai_deepseek_v4_pro_raw_model_cost_entry():
model_info = litellm.model_cost["azure_ai/deepseek-v4-pro"]
assert model_info["supported_modalities"] == ["text"]
assert model_info["supported_output_modalities"] == ["text"]
assert model_info["supports_function_calling"] is True
assert model_info["supports_reasoning"] is True
assert model_info["supports_tool_choice"] is True
@pytest.mark.parametrize(
"model_name",
["deepseek-v4-pro"],
)
def test_azure_ai_deepseek_v4_pro_cost_per_token(model_name: str):
usage = Usage(
prompt_tokens=1_000_000,
completion_tokens=1_000_000,
total_tokens=2_000_000,
)
prompt_cost, completion_cost = cost_per_token(model=model_name, usage=usage)
assert prompt_cost == pytest.approx(1.74)
assert completion_cost == pytest.approx(3.48)