feat(pricing): add groq/qwen/qwen3.6-27b to model cost map

litellm/model_prices_and_context_window_backup.json

@@ -25692,6 +25692,21 @@
         "supports_response_schema": false,
         "supports_tool_choice": true
     },
+    "groq/qwen/qwen3.6-27b": {
+        "cache_read_input_token_cost": 3e-07,
+        "input_cost_per_token": 6e-07,
+        "litellm_provider": "groq",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 3e-06,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "groq/whisper-large-v3": {
         "input_cost_per_second": 3.083e-05,
         "litellm_provider": "groq",

model_prices_and_context_window.json

@@ -25767,6 +25767,21 @@
         "supports_response_schema": false,
         "supports_tool_choice": true
     },
+    "groq/qwen/qwen3.6-27b": {
+        "cache_read_input_token_cost": 3e-07,
+        "input_cost_per_token": 6e-07,
+        "litellm_provider": "groq",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 3e-06,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "groq/whisper-large-v3": {
         "input_cost_per_second": 3.083e-05,
         "litellm_provider": "groq",

tests/test_litellm/llms/groq/test_groq_qwen3_6_27b_metadata.py

@@ -0,0 +1,60 @@
+"""
+Test Groq qwen3.6-27b model metadata in the cost map.
+"""
+
+import json
+from importlib.resources import files
+
+import pytest
+
+
+@pytest.fixture(scope="module")
+def use_local_model_cost_map():
+    monkeypatch = pytest.MonkeyPatch()
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+
+    import litellm
+    from litellm.utils import _invalidate_model_cost_lowercase_map
+
+    original_model_cost = litellm.model_cost
+    litellm.model_cost = json.loads(
+        files("litellm").joinpath("model_prices_and_context_window_backup.json").read_text(encoding="utf-8")
+    )
+    litellm.get_model_info.cache_clear()
+    _invalidate_model_cost_lowercase_map()
+    try:
+        yield litellm
+    finally:
+        litellm.model_cost = original_model_cost
+        litellm.get_model_info.cache_clear()
+        _invalidate_model_cost_lowercase_map()
+        monkeypatch.undo()
+
+
+def test_groq_qwen3_6_27b_model_info(use_local_model_cost_map):
+    model_info = use_local_model_cost_map.get_model_info(model="groq/qwen/qwen3.6-27b")
+
+    assert model_info["litellm_provider"] == "groq"
+    assert model_info["mode"] == "chat"
+    assert model_info["max_input_tokens"] == 131072
+    assert model_info["max_output_tokens"] == 16384
+    assert model_info["max_tokens"] == 16384
+    assert model_info["input_cost_per_token"] == pytest.approx(6e-07)
+    assert model_info["output_cost_per_token"] == pytest.approx(3e-06)
+    assert model_info["cache_read_input_token_cost"] == pytest.approx(3e-07)
+    assert model_info["supports_function_calling"] is True
+    assert model_info["supports_reasoning"] is True
+    assert model_info["supports_response_schema"] is True
+    assert model_info["supports_tool_choice"] is True
+    assert model_info["supports_vision"] is True
+
+
+def test_groq_qwen3_6_27b_raw_model_cost_entry(use_local_model_cost_map):
+    model_info = use_local_model_cost_map.model_cost["groq/qwen/qwen3.6-27b"]
+
+    assert model_info["litellm_provider"] == "groq"
+    assert model_info["mode"] == "chat"
+    assert model_info["input_cost_per_token"] == pytest.approx(6e-07)
+    assert model_info["output_cost_per_token"] == pytest.approx(3e-06)
+    assert model_info["cache_read_input_token_cost"] == pytest.approx(3e-07)
+    assert model_info["supports_vision"] is True