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42d8360f29
fix(together_ai): stop writing context_length as max_output_tokens in the serverless sync
241 lines
10 KiB
Python
241 lines
10 KiB
Python
import json
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from pathlib import Path
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from typing import Final
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import pytest
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from pydantic import TypeAdapter
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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REPO_ROOT: Final = Path(__file__).parents[2]
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CostMap = dict[str, dict[str, object]]
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COST_MAP_ADAPTER: Final = TypeAdapter(CostMap)
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SERVERLESS_CHAT_MODELS: Final = (
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"together_ai/moonshotai/Kimi-K3",
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"together_ai/zai-org/GLM-5.2",
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"together_ai/zai-org/GLM-5.3",
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"together_ai/zai-org/GLM-5.3-Flash",
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"together_ai/deepseek-ai/DeepSeek-V4-Pro-0813",
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"together_ai/deepseek-ai/DeepSeek-V4-Flash-0731",
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"together_ai/MiniMaxAI/MiniMax-M3",
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"together_ai/thinkingmachines/Inkling",
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"together_ai/thinkingmachines/Inkling-Small",
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"together_ai/Qwen/Qwen3.8-2.4T-A95B",
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"together_ai/Qwen/Qwen3.7-Max",
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"together_ai/Qwen/Qwen3.7-Plus",
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"together_ai/Qwen/Qwen3.6-Plus",
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"together_ai/Qwen/Qwen3.5-9B",
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"together_ai/meta-models/Muse-Glimmer-30B",
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"together_ai/google/gemma-4-31B-it",
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"together_ai/arize-ai/qwen-2-1.5b-instruct",
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"together_ai/Prism-ML/Ternary-Bonsai-27B",
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"together_ai/openai/gpt-oss-120b",
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"together_ai/openai/gpt-oss-20b",
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"together_ai/meta-llama/Llama-3.3-70B-Instruct-Turbo",
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)
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DEPRECATED_MODELS: Final = {
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"together_ai/nvidia/nemotron-3-ultra-550b-a55b": "2026-08-27",
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"together_ai/pearl-ai/gemma-4-31b-it": "2026-08-27",
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"together_ai/deepseek-ai/DeepSeek-V4-Pro": "2026-08-27",
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"together_ai/moonshotai/Kimi-K2.7-Code": "2026-08-27",
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"together_ai/google/gemma-3n-E4B-it": "2026-08-25",
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"together_ai/meta-llama/Llama-Guard-4-12B": "2026-08-25",
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"together_ai/Qwen/Qwen3-235B-A22B-Instruct-2507-tput": "2026-07-10",
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"together_ai/Qwen/Qwen3.5-397B-A17B": "2026-06-29",
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"together_ai/Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8": "2026-06-04",
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"together_ai/moonshotai/Kimi-K2.5": "2026-05-21",
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"together_ai/deepseek-ai/DeepSeek-R1": "2026-05-14",
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"together_ai/deepseek-ai/DeepSeek-V3.1": "2026-05-14",
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"together_ai/Qwen/Qwen3-235B-A22B-Thinking-2507": "2026-04-16",
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"together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1": "2026-04-16",
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"together_ai/zai-org/GLM-4.5-Air-FP8": "2026-04-02",
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"together_ai/zai-org/GLM-4.7": "2026-04-02",
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"together_ai/mistralai/Mistral-Small-24B-Instruct-2501": "2026-04-02",
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"together_ai/Qwen/Qwen3-Next-80B-A3B-Instruct": "2026-04-02",
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"together_ai/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8": "2026-03-31",
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"together_ai/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": "2026-03-06",
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"together_ai/moonshotai/Kimi-K2-Instruct-0905": "2026-03-06",
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"together_ai/meta-llama/Llama-3.2-3B-Instruct-Turbo": "2026-03-06",
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"together_ai/Qwen/Qwen3-Next-80B-A3B-Thinking": "2026-02-25",
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"together_ai/meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "2026-02-25",
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"together_ai/Qwen/Qwen3-235B-A22B-fp8-tput": "2026-02-06",
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"together_ai/meta-llama/Llama-4-Scout-17B-16E-Instruct": "2026-02-06",
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"together_ai/Qwen/Qwen2.5-72B-Instruct-Turbo": "2026-02-06",
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"together_ai/meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo": "2026-02-06",
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"together_ai/deepseek-ai/DeepSeek-R1-0528-tput": "2026-02-03",
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"together_ai/mistralai/Mistral-7B-Instruct-v0.1": "2025-11-13",
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"together_ai/meta-llama/Llama-3.3-70B-Instruct-Turbo-Free": "2025-11-13",
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}
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@pytest.fixture(scope="module")
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def cost_map() -> CostMap:
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with open(REPO_ROOT / "model_prices_and_context_window.json") as f:
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return COST_MAP_ADAPTER.validate_python(json.load(f))
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@pytest.mark.parametrize("model", SERVERLESS_CHAT_MODELS)
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def test_together_serverless_chat_model_is_mapped(cost_map: CostMap, model: str):
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info = cost_map.get(model)
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assert info is not None, f"{model} missing from model_prices_and_context_window.json"
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assert info["litellm_provider"] == "together_ai"
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assert info["mode"] == "chat"
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assert info["input_cost_per_token"] >= 0
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assert info["output_cost_per_token"] >= info["input_cost_per_token"]
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assert "deprecation_date" not in info
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routed_model, provider, _, _ = get_llm_provider(model=model)
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assert routed_model == model.removeprefix("together_ai/")
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assert provider == "together_ai"
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def test_together_kimi_k3_pricing_and_capabilities(cost_map: CostMap):
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info = cost_map["together_ai/moonshotai/Kimi-K3"]
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assert info["input_cost_per_token"] == 3e-06
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assert info["output_cost_per_token"] == 1.5e-05
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assert info["max_input_tokens"] == 1048576
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assert info["supports_function_calling"] is True
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assert info["supports_tool_choice"] is True
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assert info["supports_response_schema"] is True
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assert info["supports_vision"] is True
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assert info["supports_reasoning"] is True
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def test_together_glm_52_pricing(cost_map: CostMap):
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info = cost_map["together_ai/zai-org/GLM-5.2"]
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assert info["input_cost_per_token"] == 1.4e-06
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assert info["output_cost_per_token"] == 4.4e-06
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assert info["max_input_tokens"] == 1048575
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assert info["max_output_tokens"] == 128000
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assert info["supports_function_calling"] is True
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assert info["supports_reasoning"] is True
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def test_together_glm_53_flash_pricing_and_capabilities(cost_map: CostMap):
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info = cost_map["together_ai/zai-org/GLM-5.3-Flash"]
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assert info["input_cost_per_token"] == 1.5e-07
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assert info["output_cost_per_token"] == 5e-07
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assert info["cache_read_input_token_cost"] == 3e-08
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assert info["max_input_tokens"] == 1048575
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assert info["max_output_tokens"] == 128000
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assert info["supports_function_calling"] is True
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assert info["supports_parallel_function_calling"] is True
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assert info["supports_prompt_caching"] is True
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assert info["supports_tool_choice"] is True
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assert info["supports_response_schema"] is True
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assert info["supports_vision"] is True
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assert info["supports_reasoning"] is True
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def test_together_chat_entries_never_carry_context_length_as_output_ceiling(cost_map: CostMap):
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inflated = sorted(
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model
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for model, info in cost_map.items()
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if info.get("litellm_provider") == "together_ai"
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and info.get("mode") == "chat"
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and "max_output_tokens" in info
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and info["max_output_tokens"] == info.get("max_input_tokens")
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)
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assert inflated == []
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def test_together_multilingual_e5_embedding_entry(cost_map: CostMap):
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info = cost_map["together_ai/intfloat/multilingual-e5-large-instruct"]
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assert info["mode"] == "embedding"
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assert info["input_cost_per_token"] == 2e-08
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assert info["max_input_tokens"] == 514
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assert info["output_vector_size"] == 1024
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def test_together_llama_33_70b_repriced_to_current_together_rate(cost_map: CostMap):
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info = cost_map["together_ai/meta-llama/Llama-3.3-70B-Instruct-Turbo"]
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assert info["input_cost_per_token"] == 1.04e-06
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assert info["output_cost_per_token"] == 1.04e-06
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assert info["max_input_tokens"] == 131072
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@pytest.mark.parametrize("model", sorted(DEPRECATED_MODELS))
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def test_together_deprecated_model_carries_deprecation_date(cost_map: CostMap, model: str):
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info = cost_map.get(model)
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assert info is not None, f"{model} missing from model_prices_and_context_window.json"
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assert info.get("deprecation_date") == DEPRECATED_MODELS[model]
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def _successor(info: dict[str, object]) -> str | None:
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metadata = info.get("metadata")
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if not isinstance(metadata, dict):
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return None
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successor = metadata.get("successor")
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return successor if isinstance(successor, str) else None
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def test_together_successor_metadata_points_at_live_models(cost_map: CostMap):
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successors = {
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model: successor
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for model, info in cost_map.items()
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if model.startswith("together_ai/") and (successor := _successor(info)) is not None
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}
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assert len(successors) >= 10
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for model, successor in successors.items():
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target = cost_map.get(successor)
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assert target is not None, f"{model} names successor {successor} that is not in the map"
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assert "deprecation_date" not in target, f"{model} names deprecated successor {successor}"
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def test_together_backup_cost_map_in_sync(cost_map: CostMap):
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with open(REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json") as f:
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backup = COST_MAP_ADAPTER.validate_python(json.load(f))
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together_main = {k: v for k, v in cost_map.items() if k.startswith("together_ai/")}
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together_backup = {k: v for k, v in backup.items() if k.startswith("together_ai/")}
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assert together_backup == together_main
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CACHED_INPUT_MODELS: Final = (
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"together_ai/moonshotai/Kimi-K3",
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"together_ai/zai-org/GLM-5.2",
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"together_ai/meta-models/Muse-Glimmer-30B",
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"together_ai/Qwen/Qwen3.8-2.4T-A95B",
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"together_ai/deepseek-ai/DeepSeek-V4-Pro-0813",
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"together_ai/deepseek-ai/DeepSeek-V4-Flash-0731",
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"together_ai/thinkingmachines/Inkling",
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"together_ai/MiniMaxAI/MiniMax-M3",
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"together_ai/thinkingmachines/Inkling-Small",
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"together_ai/moonshotai/Kimi-K2.7-Code",
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"together_ai/deepseek-ai/DeepSeek-V4-Pro",
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"together_ai/nvidia/nemotron-3-ultra-550b-a55b",
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"together_ai/Qwen/Qwen3.7-Max",
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)
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@pytest.mark.parametrize("model", CACHED_INPUT_MODELS)
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def test_together_cached_input_model_carries_cache_read_pricing(cost_map: CostMap, model: str):
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info = cost_map.get(model)
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assert info is not None, f"{model} missing from model_prices_and_context_window.json"
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assert info.get("supports_prompt_caching") is True
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cache_read = info.get("cache_read_input_token_cost")
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assert isinstance(cache_read, float)
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assert 0 < cache_read < info["input_cost_per_token"]
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assert "cache_creation_input_token_cost" not in info
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def test_together_prompt_caching_flag_implies_cache_read_rate(cost_map: CostMap):
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for model, info in cost_map.items():
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if model.startswith("together_ai/") and info.get("supports_prompt_caching"):
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assert "cache_read_input_token_cost" in info, f"{model} flags caching without a cache read rate"
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def test_together_deepseek_v4_flash_cache_read_rate(cost_map: CostMap):
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info = cost_map["together_ai/deepseek-ai/DeepSeek-V4-Flash-0731"]
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assert info["input_cost_per_token"] == 1.4e-07
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assert info["cache_read_input_token_cost"] == 3e-08
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assert info["output_cost_per_token"] == 2.8e-07
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def test_together_qwen_37_max_repriced_to_current_together_rate(cost_map: CostMap):
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info = cost_map["together_ai/Qwen/Qwen3.7-Max"]
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assert info["input_cost_per_token"] == 2.5e-06
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assert info["output_cost_per_token"] == 7.5e-06
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assert info["cache_read_input_token_cost"] == 5e-07
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