feat(models): add Qwen3.8 27B preset

app.py

@@ -707,6 +707,7 @@ PROMPT_VOLUMES = {
 _NEEDS_QUANTIZATION = {
     "openai/gpt-oss-20b",
     "Qwen/Qwen3-30B-A3B",
+    "Qwen/Qwen3.8-27B",
     "zai-org/GLM-4.7-Flash",
     "Qwen/Qwen3.5-397B-A17B",
     "zai-org/GLM-5",

obliteratus/presets.py

@@ -208,6 +208,15 @@ _PRESETS_LIST = [
         recommended_dtype="bfloat16",
         recommended_quantization="4bit",
     ),
+    ModelPreset(
+        name="Qwen3.8-27B",
+        hf_id="Qwen/Qwen3.8-27B",
+        description="Qwen3.8 27B dense multimodal model. 262K context, think/non-think modes. Apache 2.0.",
+        tier="large",
+        params="27B",
+        recommended_dtype="bfloat16",
+        recommended_quantization="4bit",
+    ),
     ModelPreset(
         name="Qwen3.8 2.4T-A95B",
         hf_id="Qwen/Qwen3.8-2.4T-A95B",

tests/test_bestiary_contracts.py

@@ -24,6 +24,7 @@ class Preset:
 @pytest.mark.parametrize(
     "model_id",
     [
+        "Qwen/Qwen3.8-27B",
         "Qwen/Qwen3.8-2.4T-A95B",
         "deepseek-ai/DeepSeek-V4-Flash-0731",
         "deepseek-ai/DeepSeek-V4-Pro-0813",
@@ -43,6 +44,17 @@ def test_current_verified_models_are_curated(model_id: str) -> None:
     assert model_id in presets.MODEL_PRESETS
 
 
+def test_qwen38_27b_preset_matches_the_published_model_contract() -> None:
+    preset = presets.MODEL_PRESETS["Qwen/Qwen3.8-27B"]
+
+    assert preset.name == "Qwen3.8-27B"
+    assert preset.params == "27B"
+    assert preset.tier == "large"
+    assert preset.recommended_dtype == "bfloat16"
+    assert preset.recommended_quantization == "4bit"
+    assert preset.gated is False
+
+
 @pytest.mark.parametrize(
     "size, expected",
     [