diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b73feae90d3..650415279cb 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -29046,16 +29046,36 @@ "supports_tool_choice": true }, "mistral/zai-glm-5-2": { + "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.4e-06, "litellm_provider": "mistral", - "max_input_tokens": 1000000, - "max_output_tokens": 128000, - "max_tokens": 128000, + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, "source": "https://docs.mistral.ai/models/zai-glm-5-2", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "mistral/glm-5-2": { + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "mistral", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://docs.mistral.ai/models/zai-glm-5-2", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b73feae90d3..650415279cb 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -29046,16 +29046,36 @@ "supports_tool_choice": true }, "mistral/zai-glm-5-2": { + "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.4e-06, "litellm_provider": "mistral", - "max_input_tokens": 1000000, - "max_output_tokens": 128000, - "max_tokens": 128000, + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, "source": "https://docs.mistral.ai/models/zai-glm-5-2", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "mistral/glm-5-2": { + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "mistral", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://docs.mistral.ai/models/zai-glm-5-2", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, diff --git a/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py b/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py new file mode 100644 index 00000000000..ad1f3b06e15 --- /dev/null +++ b/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py @@ -0,0 +1,103 @@ +import json +from pathlib import Path + +import pytest + +import litellm +from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider +from litellm.types.utils import PromptTokensDetailsWrapper, Usage +from litellm.utils import supports_prompt_caching, supports_reasoning + +REPO_ROOT = Path(__file__).parents[2] +MAIN_PATH = REPO_ROOT / "model_prices_and_context_window.json" +BACKUP_PATH = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json" + +GLM_5_2_MODELS = ("mistral/zai-glm-5-2", "mistral/glm-5-2") + +INPUT_COST = 1.4e-06 +CACHED_INPUT_COST = 1.4e-07 +OUTPUT_COST = 4.4e-06 + + +def _load(path): + with open(path) as f: + return json.load(f) + + +@pytest.fixture +def local_model_cost_map(monkeypatch): + """Force get_model_info to resolve against the in-repo cost map instead of the + remote one fetched at import time, which still carries the pre-merge pricing.""" + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + litellm.get_model_info.cache_clear() + yield + litellm.get_model_info.cache_clear() + + +@pytest.mark.parametrize("model", GLM_5_2_MODELS) +def test_zai_glm_5_2_specs(model): + info = _load(MAIN_PATH).get(model) + assert info is not None, f"{model} missing from model_prices_and_context_window.json" + + assert info["litellm_provider"] == "mistral" + assert info["mode"] == "chat" + + assert info["input_cost_per_token"] == INPUT_COST + assert info["output_cost_per_token"] == OUTPUT_COST + assert info["cache_read_input_token_cost"] == CACHED_INPUT_COST + + assert info["max_input_tokens"] == 1048576 + assert info["max_output_tokens"] == 131072 + assert info["max_tokens"] == 131072 + + assert info["supports_assistant_prefill"] is True + assert info["supports_function_calling"] is True + assert info["supports_prompt_caching"] is True + assert info["supports_reasoning"] is True + assert info["supports_response_schema"] is True + assert info["supports_tool_choice"] is True + + routed_model, provider, _, _ = get_llm_provider(model=model) + assert routed_model == model.split("/", 1)[1] + assert provider == "mistral" + + +@pytest.mark.parametrize("model", GLM_5_2_MODELS) +def test_zai_glm_5_2_capabilities_are_visible_to_callers(local_model_cost_map, model): + """Mistral advertises reasoning and prompt caching on this model, so the helpers + every caller checks before sending a request must say so too.""" + assert supports_reasoning(model=model) is True + assert supports_prompt_caching(model=model) is True + + info = litellm.get_model_info(model=model) + assert info["max_input_tokens"] == 1048576 + assert info["max_output_tokens"] == 131072 + + +@pytest.mark.parametrize("model", GLM_5_2_MODELS) +def test_cached_prompt_tokens_bill_at_the_cached_rate(local_model_cost_map, model): + """A cache hit reports its reused tokens under prompt_tokens_details, and those + tokens cost a tenth of the input rate, not the full rate and not nothing.""" + usage = Usage( + prompt_tokens=21010, + completion_tokens=100, + total_tokens=21110, + prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=20992), + ) + + prompt_cost, completion_cost = litellm.cost_per_token( + model=model, usage_object=usage, custom_llm_provider="mistral" + ) + + assert prompt_cost == pytest.approx(18 * INPUT_COST + 20992 * CACHED_INPUT_COST) + assert completion_cost == pytest.approx(100 * OUTPUT_COST) + + +@pytest.mark.parametrize("model", GLM_5_2_MODELS) +def test_backup_matches_main(model): + """Ensure the bundled (backup) cost map stays in sync with the canonical file.""" + main_cost = _load(MAIN_PATH) + backup_cost = _load(BACKUP_PATH) + + assert backup_cost.get(model) == main_cost.get(model), f"{model} differs between main and backup model cost maps"