fix(mistral): correct zai-glm-5-2 limits, add cached-input price and glm-5-2 alias

Mistral's live /v1/models reports max_context_length 1048576 and capabilities.reasoning
true for zai-glm-5-2, and its docs price cached input at $0.14/M. Without
cache_read_input_token_cost LiteLLM billed every cached prompt token at $0, so a repeat
request against a 21k-token cached prefix logged $0.0000135 instead of its real cost.

Mistral also serves the model under the short glm-5-2 name, which had no cost map entry
at all and therefore no pricing, so add it alongside.

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
     },

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
     },

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"