diff --git a/litellm/llms/azure_ai/cost_calculator.py b/litellm/llms/azure_ai/cost_calculator.py index 95f536296a2..141148f06e7 100644 --- a/litellm/llms/azure_ai/cost_calculator.py +++ b/litellm/llms/azure_ai/cost_calculator.py @@ -56,6 +56,27 @@ def calculate_azure_model_router_flat_cost(model: str, prompt_tokens: int) -> fl return 0.0 +ROUTER_FEE_ENTRY_NAMES: Final = frozenset({"model-router", "model_router"}) + + +def _prices_router_fee_itself(model: str) -> bool: + return model.lower().rsplit("/", 1)[-1] in ROUTER_FEE_ENTRY_NAMES + + +def _base_cost_per_token(model: str, usage: Usage, service_tier: str | None) -> tuple[float, float] | None: + try: + return generic_cost_per_token( + model=model, usage=usage, custom_llm_provider="azure_ai", service_tier=service_tier + ) + except Exception as e: + if not _is_azure_model_router(model): + raise + verbose_logger.debug( + "Azure AI Model Router: model '%s' not in cost map, calculating routing flat cost only. Error: %s", model, e + ) + return None + + def cost_per_token( model: str, usage: Usage, @@ -66,9 +87,9 @@ def cost_per_token( """ Calculate the cost per token for Azure AI models. - For Azure AI Foundry Model Router: - - Adds a flat cost of $0.14 per million input tokens (from model_prices_and_context_window.json) - - Plus the cost of the actual model used (handled by generic_cost_per_token) + For Azure AI Foundry Model Router the routing fee (the azure_ai/model_router entry, $0.14 per + million input tokens) is added on top of the routed model's cost. When the response model is + the router entry itself, generic_cost_per_token has already charged that fee. Args: model: str, the model name without provider prefix (from response) @@ -83,49 +104,12 @@ def cost_per_token( ValueError: If the model is not found in the cost map and cost cannot be calculated (except for Model Router models where we return just the routing flat cost) """ - prompt_cost = 0.0 - completion_cost = 0.0 - - # Determine if this was a model router request - # Check both the response model and the request model is_router_request: Final = _is_azure_model_router(model) or ( request_model is not None and _is_azure_model_router(request_model) ) - - # Calculate base cost using generic cost calculator - # This may raise an exception if the model is not in the cost map - try: - prompt_cost, completion_cost = generic_cost_per_token( - model=model, - usage=usage, - custom_llm_provider="azure_ai", - service_tier=service_tier, - ) - except Exception as e: - # For Model Router, the model name (e.g., "azure-model-router") may not be in the cost map - # because it's a routing service, not an actual model. In this case, we continue - # to calculate just the routing flat cost. - if not _is_azure_model_router(model): - # Re-raise for non-router models - they should have pricing defined - raise - verbose_logger.debug( - "Azure AI Model Router: model '%s' not in cost map, calculating routing flat cost only. Error: %s", model, e - ) - - # Add flat cost for Azure Model Router - # The flat cost is defined in model_prices_and_context_window.json for azure_ai/model_router - if is_router_request: - # Use the request model for flat cost calculation if available, otherwise use response model - router_model_for_calc: Final = request_model if request_model else model - router_flat_cost: Final = calculate_azure_model_router_flat_cost(router_model_for_calc, usage.prompt_tokens) - - if router_flat_cost > 0: - verbose_logger.debug( - f"Azure AI Model Router flat cost: ${router_flat_cost:.6f} " - f"({usage.prompt_tokens} tokens × ${router_flat_cost / usage.prompt_tokens:.9f}/token)" - ) - - # Add flat cost to prompt cost - prompt_cost += router_flat_cost - - return prompt_cost, completion_cost + base_cost: Final = _base_cost_per_token(model=model, usage=usage, service_tier=service_tier) + prompt_cost, completion_cost = base_cost if base_cost is not None else (0.0, 0.0) + if not is_router_request or (base_cost is not None and _prices_router_fee_itself(model)): + return prompt_cost, completion_cost + router_flat_cost: Final = calculate_azure_model_router_flat_cost(request_model or model, usage.prompt_tokens) + return prompt_cost + router_flat_cost, completion_cost diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b1ffc1583e4..6649fa831d7 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -3581,6 +3581,82 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, + "azure_ai/gpt-chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": 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 + }, + "azure_ai/codex-mini": { + "cache_read_input_token_cost": 3.75e-07, + "deprecation_date": "2026-11-15", + "input_cost_per_token": 1.5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "responses", + "output_cost_per_token": 6e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": 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 + }, + "azure_ai/whisper": { + "deprecation_date": "2026-12-15", + "input_cost_per_second": 0.0001, + "litellm_provider": "azure_ai", + "mode": "audio_transcription", + "output_cost_per_second": 0.0001, + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/" + }, "azure_ai/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, @@ -3991,6 +4067,17 @@ "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/", "comment": "Flat cost of $0.14 per M input tokens for Azure AI Foundry Model Router infrastructure. Use pattern: azure_ai/model_router/ where deployment-name is your Azure deployment (e.g., azure-model-router)" }, + "azure_ai/model-router": { + "input_cost_per_token": 1.4e-07, + "output_cost_per_token": 0, + "litellm_provider": "azure_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/", + "comment": "Catalog-name twin of azure_ai/model_router: the flat $0.14 per M input tokens is the router's own fee, the routed model is priced on top of it" + }, "azure/eu/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", "cache_read_input_token_cost": 1.375e-06, @@ -10302,6 +10389,18 @@ "/v1/ocr" ] }, + "azure_ai/cohere-command-a": { + "input_cost_per_token": 2.5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 131072, + "max_output_tokens": 4096, + "max_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 1e-05, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/cohere/", + "supports_function_calling": true, + "supports_tool_choice": true + }, "azure_ai/doc-intelligence/prebuilt-read": { "litellm_provider": "azure_ai", "ocr_cost_per_page": 0.0015, @@ -10653,6 +10752,37 @@ "supports_vision": true, "supports_web_search": true }, + "azure_ai/grok-4-20-reasoning": { + "input_cost_per_token": 1.25e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 262000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/grok/", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_reasoning": true + }, + "azure_ai/grok-4-20-non-reasoning": { + "input_cost_per_token": 1.25e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 262000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/grok/", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure_ai/grok-4-fast-non-reasoning": { "deprecation_date": "2026-05-01", "input_cost_per_token": 2e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b1ffc1583e4..6649fa831d7 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -3581,6 +3581,82 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, + "azure_ai/gpt-chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": 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 + }, + "azure_ai/codex-mini": { + "cache_read_input_token_cost": 3.75e-07, + "deprecation_date": "2026-11-15", + "input_cost_per_token": 1.5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "responses", + "output_cost_per_token": 6e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": 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 + }, + "azure_ai/whisper": { + "deprecation_date": "2026-12-15", + "input_cost_per_second": 0.0001, + "litellm_provider": "azure_ai", + "mode": "audio_transcription", + "output_cost_per_second": 0.0001, + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/" + }, "azure_ai/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, @@ -3991,6 +4067,17 @@ "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/", "comment": "Flat cost of $0.14 per M input tokens for Azure AI Foundry Model Router infrastructure. Use pattern: azure_ai/model_router/ where deployment-name is your Azure deployment (e.g., azure-model-router)" }, + "azure_ai/model-router": { + "input_cost_per_token": 1.4e-07, + "output_cost_per_token": 0, + "litellm_provider": "azure_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/", + "comment": "Catalog-name twin of azure_ai/model_router: the flat $0.14 per M input tokens is the router's own fee, the routed model is priced on top of it" + }, "azure/eu/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", "cache_read_input_token_cost": 1.375e-06, @@ -10302,6 +10389,18 @@ "/v1/ocr" ] }, + "azure_ai/cohere-command-a": { + "input_cost_per_token": 2.5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 131072, + "max_output_tokens": 4096, + "max_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 1e-05, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/cohere/", + "supports_function_calling": true, + "supports_tool_choice": true + }, "azure_ai/doc-intelligence/prebuilt-read": { "litellm_provider": "azure_ai", "ocr_cost_per_page": 0.0015, @@ -10653,6 +10752,37 @@ "supports_vision": true, "supports_web_search": true }, + "azure_ai/grok-4-20-reasoning": { + "input_cost_per_token": 1.25e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 262000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/grok/", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_reasoning": true + }, + "azure_ai/grok-4-20-non-reasoning": { + "input_cost_per_token": 1.25e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 262000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/grok/", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure_ai/grok-4-fast-non-reasoning": { "deprecation_date": "2026-05-01", "input_cost_per_token": 2e-07, diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_cost_calculator.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_cost_calculator.py index 9612d97d946..80cd99bd46b 100644 --- a/tests/test_litellm/llms/azure_ai/test_azure_ai_cost_calculator.py +++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_cost_calculator.py @@ -528,3 +528,29 @@ def test_mai_thinking_1_model_info_and_cost(local_model_cost_map): assert model_info["supports_function_calling"] is True assert prompt_cost == pytest.approx(2.0) assert completion_cost == pytest.approx(8.0) + + +@pytest.mark.usefixtures("local_model_cost_map") +@pytest.mark.parametrize("router_entry_name", ["model_router", "model-router"]) +def test_router_entry_as_response_model_charges_the_fee_once(router_entry_name: str) -> None: + usage = Usage(prompt_tokens=1_000_000, completion_tokens=0, total_tokens=1_000_000) + prompt_cost, completion_cost = cost_per_token(model=router_entry_name, usage=usage) + assert prompt_cost == pytest.approx(0.14, rel=1e-9) + assert completion_cost == 0.0 + + +@pytest.mark.usefixtures("local_model_cost_map") +def test_unmapped_router_deployment_name_still_charges_the_fee() -> None: + usage = Usage(prompt_tokens=1_000_000, completion_tokens=0, total_tokens=1_000_000) + prompt_cost, completion_cost = cost_per_token(model="azure-model-router", usage=usage) + assert prompt_cost == pytest.approx(0.14, rel=1e-9) + assert completion_cost == 0.0 + + +@pytest.mark.usefixtures("local_model_cost_map") +def test_routed_model_response_adds_the_fee_on_top() -> None: + usage = Usage(prompt_tokens=1_000_000, completion_tokens=0, total_tokens=1_000_000) + routed_prompt_cost, _ = cost_per_token(model="gpt-5-nano", usage=usage) + prompt_cost, _ = cost_per_token(model="gpt-5-nano", usage=usage, request_model="azure_ai/model-router") + assert routed_prompt_cost > 0 + assert prompt_cost == pytest.approx(routed_prompt_cost + 0.14, rel=1e-9) diff --git a/tests/test_litellm/test_azure_ai_foundry_catalog_model_metadata.py b/tests/test_litellm/test_azure_ai_foundry_catalog_model_metadata.py new file mode 100644 index 00000000000..9c5ca26a89c --- /dev/null +++ b/tests/test_litellm/test_azure_ai_foundry_catalog_model_metadata.py @@ -0,0 +1,176 @@ +from dataclasses import dataclass +from pathlib import Path +from typing import Final + +import pytest +from pydantic import TypeAdapter + +from litellm import cost_per_token, get_model_info +from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider + +REPO_ROOT: Final = Path(__file__).parents[2] +COST_MAP_ADAPTER: Final = TypeAdapter(dict[str, dict[str, object]]) +AZURE_OPENAI_PRICING: Final = "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/" +FOUNDRY_AOAI_PRICING: Final = "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/" +FOUNDRY_COHERE_PRICING: Final = "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/cohere/" +FOUNDRY_GROK_PRICING: Final = "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/grok/" + + +@dataclass(frozen=True, slots=True) +class TokenPricedCatalogModel: + catalog_name: str + mode: str + source: str + input_cost_per_token: float + output_cost_per_token: float + max_input_tokens: int + max_output_tokens: int + cache_read_input_token_cost: float | None + supported_flags: tuple[str, ...] + + +TOKEN_PRICED_MODELS: Final = ( + TokenPricedCatalogModel( + catalog_name="gpt-chat-latest", + mode="chat", + source=AZURE_OPENAI_PRICING, + input_cost_per_token=5e-06, + output_cost_per_token=3e-05, + max_input_tokens=200000, + max_output_tokens=128000, + cache_read_input_token_cost=5e-07, + supported_flags=( + "supports_function_calling", + "supports_prompt_caching", + "supports_reasoning", + "supports_response_schema", + "supports_tool_choice", + "supports_vision", + "supports_web_search", + ), + ), + TokenPricedCatalogModel( + catalog_name="codex-mini", + mode="responses", + source=AZURE_OPENAI_PRICING, + input_cost_per_token=1.5e-06, + output_cost_per_token=6e-06, + max_input_tokens=200000, + max_output_tokens=100000, + cache_read_input_token_cost=3.75e-07, + supported_flags=("supports_function_calling", "supports_prompt_caching", "supports_reasoning", "supports_vision"), + ), + TokenPricedCatalogModel( + catalog_name="model-router", + mode="chat", + source=FOUNDRY_AOAI_PRICING, + input_cost_per_token=1.4e-07, + output_cost_per_token=0.0, + max_input_tokens=1048576, + max_output_tokens=32768, + cache_read_input_token_cost=None, + supported_flags=(), + ), + TokenPricedCatalogModel( + catalog_name="cohere-command-a", + mode="chat", + source=FOUNDRY_COHERE_PRICING, + input_cost_per_token=2.5e-06, + output_cost_per_token=1e-05, + max_input_tokens=131072, + max_output_tokens=4096, + cache_read_input_token_cost=None, + supported_flags=("supports_function_calling", "supports_tool_choice"), + ), + TokenPricedCatalogModel( + catalog_name="grok-4-20-reasoning", + mode="chat", + source=FOUNDRY_GROK_PRICING, + input_cost_per_token=1.25e-06, + output_cost_per_token=2.5e-06, + max_input_tokens=262000, + max_output_tokens=8192, + cache_read_input_token_cost=None, + supported_flags=( + "supports_function_calling", + "supports_reasoning", + "supports_response_schema", + "supports_tool_choice", + "supports_vision", + "supports_web_search", + ), + ), + TokenPricedCatalogModel( + catalog_name="grok-4-20-non-reasoning", + mode="chat", + source=FOUNDRY_GROK_PRICING, + input_cost_per_token=1.25e-06, + output_cost_per_token=2.5e-06, + max_input_tokens=262000, + max_output_tokens=8192, + cache_read_input_token_cost=None, + supported_flags=( + "supports_function_calling", + "supports_response_schema", + "supports_tool_choice", + "supports_vision", + "supports_web_search", + ), + ), +) +CATALOG_NAMES: Final = tuple(spec.catalog_name for spec in TOKEN_PRICED_MODELS) + ("whisper",) + + +def _cost_map_entry(path: Path, catalog_name: str) -> dict[str, object]: + return COST_MAP_ADAPTER.validate_json(path.read_bytes())[f"azure_ai/{catalog_name}"] + + +@pytest.mark.usefixtures("local_model_cost_map") +@pytest.mark.parametrize("spec", TOKEN_PRICED_MODELS, ids=lambda spec: spec.catalog_name) +def test_azure_ai_catalog_name_is_priced_and_routed(spec: TokenPricedCatalogModel) -> None: + routed_model, provider, _, _ = get_llm_provider(model=f"azure_ai/{spec.catalog_name}") + assert (routed_model, provider) == (spec.catalog_name, "azure_ai") + + info = get_model_info(model=routed_model, custom_llm_provider=provider) + assert info["litellm_provider"] == "azure_ai" + assert info["mode"] == spec.mode + assert info["input_cost_per_token"] == spec.input_cost_per_token + assert info["output_cost_per_token"] == spec.output_cost_per_token + assert info["cache_read_input_token_cost"] == spec.cache_read_input_token_cost + assert info["max_input_tokens"] == spec.max_input_tokens + assert info["max_output_tokens"] == spec.max_output_tokens + assert info["max_tokens"] == spec.max_output_tokens + for flag in spec.supported_flags: + assert info[flag] is True, flag + + +@pytest.mark.usefixtures("local_model_cost_map") +@pytest.mark.parametrize( + "spec", [spec for spec in TOKEN_PRICED_MODELS if spec.catalog_name != "model-router"], ids=lambda spec: spec.catalog_name +) +def test_azure_ai_catalog_name_costs_a_million_tokens_at_list_price(spec: TokenPricedCatalogModel) -> None: + prompt_cost, completion_cost = cost_per_token( + model=f"azure_ai/{spec.catalog_name}", prompt_tokens=1_000_000, completion_tokens=1_000_000 + ) + assert prompt_cost == pytest.approx(spec.input_cost_per_token * 1_000_000) + assert completion_cost == pytest.approx(spec.output_cost_per_token * 1_000_000) + + +@pytest.mark.usefixtures("local_model_cost_map") +def test_azure_ai_whisper_catalog_name_is_priced_per_second() -> None: + routed_model, provider, _, _ = get_llm_provider(model="azure_ai/whisper") + assert (routed_model, provider) == ("whisper", "azure_ai") + + info = get_model_info(model=routed_model, custom_llm_provider=provider) + assert info["mode"] == "audio_transcription" + assert info["input_cost_per_second"] == 0.0001 + assert info["output_cost_per_second"] == 0.0001 + + +@pytest.mark.parametrize("catalog_name", CATALOG_NAMES) +def test_azure_ai_catalog_entry_source_and_backup_match(catalog_name: str) -> None: + main_entry = _cost_map_entry(REPO_ROOT / "model_prices_and_context_window.json", catalog_name) + backup_entry = _cost_map_entry(REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json", catalog_name) + + assert str(main_entry["source"]).startswith("https://azure.microsoft.com/en-us/pricing/details/") + assert backup_entry == main_entry