Reject quant values that cannot be applied

README.md

@@ -126,6 +126,8 @@ For reduced memory usage, use quantized models:
 whisper = LightningWhisperMLX(model="distil-large-v3", quant="4bit")
 ```
 
+`quant` accepts `"4bit"` or `"8bit"` and is available for `tiny`, `small`, `medium`, `large-v3` and `distil-large-v3`. Other models raise a `ValueError` rather than silently loading full precision.
+
 ## Batch Size Recommendations
 
 | Model | Recommended batch_size | Memory Usage |

tests/test_utils.py

@@ -0,0 +1,50 @@
+"""Model name resolution."""
+
+import pytest
+
+from whisper_mlx import LightningWhisperMLX
+from whisper_mlx.utils import QUANT_REPOS, resolve_model_path
+
+
+def test_names_resolve_to_repos():
+    assert resolve_model_path("turbo") == "mlx-community/whisper-turbo"
+    assert resolve_model_path("tiny") == "mlx-community/whisper-tiny-mlx"
+
+
+def test_repo_paths_pass_through():
+    assert resolve_model_path("someone/whisper-custom") == "someone/whisper-custom"
+
+
+def test_unknown_name_is_rejected():
+    with pytest.raises(ValueError, match="Unknown model"):
+        resolve_model_path("gigantic")
+
+
+@pytest.mark.parametrize("model", sorted(QUANT_REPOS))
+@pytest.mark.parametrize("quant", ["4bit", "8bit"])
+def test_quantized_builds_resolve(model, quant):
+    assert resolve_model_path(model, quant) == QUANT_REPOS[model][quant]
+
+
+def test_unknown_quant_is_rejected():
+    with pytest.raises(ValueError, match="Unknown quant '3bit'"):
+        resolve_model_path("tiny", "3bit")
+
+
+def test_quant_for_model_without_quantized_build_is_rejected():
+    with pytest.raises(ValueError, match="No 4bit build of 'turbo'"):
+        resolve_model_path("turbo", "4bit")
+
+
+def test_quant_with_repo_path_is_rejected():
+    with pytest.raises(ValueError, match="quant only applies to model names"):
+        resolve_model_path("someone/whisper-custom", "8bit")
+
+
+def test_empty_quant_means_full_precision():
+    assert resolve_model_path("tiny", None) == resolve_model_path("tiny", "")
+
+
+def test_lightning_wrapper_rejects_unavailable_quant():
+    with pytest.raises(ValueError, match="No 4bit build"):
+        LightningWhisperMLX(model="turbo", quant="4bit")

whisper_mlx/lightning.py

@@ -56,7 +56,8 @@ def __init__(
             Recommended: 12 for distil models, 6 for large models.
 
         quant : str, optional
-            Quantization level: "4bit" or "8bit". Only supported for some models.
+            Quantization level: "4bit" or "8bit". Available for tiny, small,
+            medium, large-v3 and distil-large-v3; raises ValueError otherwise.
         """
         if batch_size < 1:
             raise ValueError(f"batch_size must be >= 1, got {batch_size}")

whisper_mlx/utils.py

@@ -60,6 +60,7 @@ def format_timestamp(
 }
 
 # Quantized model repos
+QUANT_LEVELS = ("4bit", "8bit")
 QUANT_REPOS = {
     "tiny": {
         "4bit": "mlx-community/whisper-tiny-mlx-4bit",
@@ -95,7 +96,8 @@ def resolve_model_path(
     model : str
         Model name (e.g., "tiny", "turbo") or HuggingFace repo path
     quant : str, optional
-        Quantization level: "4bit" or "8bit"
+        Quantization level: "4bit" or "8bit". Only models listed in
+        QUANT_REPOS have quantized builds.
 
     Returns
     -------
@@ -105,11 +107,25 @@ def resolve_model_path(
     Raises
     ------
     ValueError
-        If model name is unknown
+        If the model name is unknown, or quant is invalid or not available
+        for the model
     """
-    # Check quantized repos first
-    if quant and model in QUANT_REPOS and quant in QUANT_REPOS[model]:
-        return QUANT_REPOS[model][quant]
+    if quant:
+        if quant not in QUANT_LEVELS:
+            raise ValueError(
+                f"Unknown quant {quant!r}; expected one of {list(QUANT_LEVELS)}"
+            )
+        if model in QUANT_REPOS and quant in QUANT_REPOS[model]:
+            return QUANT_REPOS[model][quant]
+        if "/" in model:
+            raise ValueError(
+                "quant only applies to model names; pass the quantized repo "
+                f"path as model instead of {model!r}"
+            )
+        raise ValueError(
+            f"No {quant} build of {model!r}. Models with quantized builds: "
+            f"{list(QUANT_REPOS)}"
+        )
 
     # Check standard repos
     if model in MODEL_REPOS: