diff --git a/nemoguardrails/embeddings/providers/fastembed.py b/nemoguardrails/embeddings/providers/fastembed.py
index e4956626c7..a124f783fd 100644
--- a/nemoguardrails/embeddings/providers/fastembed.py
+++ b/nemoguardrails/embeddings/providers/fastembed.py
@@ -19,6 +19,13 @@
 from .base import EmbeddingModel
 
 
+def _is_missing_onnx_model_error(ex: Exception) -> bool:
+    message = str(ex)
+    return "model.onnx" in message and (
+        "Could not find model.onnx in" in message or "NO_SUCHFILE" in message or "File doesn't exist" in message
+    )
+
+
 def get_executor():
     from . import embeddings_executor
 
@@ -51,14 +58,16 @@ def __init__(self, embedding_model: str, **kwargs):
 
         try:
             self.model = Embedding(embedding_model, **kwargs)
-        except ValueError as ex:
+        except Exception as ex:
             # Sometimes the cached model in the temporary folder gets removed,
             # but the folder still exists, which causes an error. In this case,
             # we fall back to an explicit cache directory.
-            if "Could not find model.onnx in" in str(ex):
-                self.model = Embedding(embedding_model, cache_dir=".cache", **kwargs)
+            if _is_missing_onnx_model_error(ex):
+                fallback_kwargs = dict(kwargs)
+                fallback_kwargs["cache_dir"] = ".cache"
+                self.model = Embedding(embedding_model, **fallback_kwargs)
             else:
-                raise ex
+                raise
 
         # Get the embedding dimension of the model
         self.embedding_size = len(list(self.model.embed("test"))[0].tolist())
diff --git a/tests/test_embeddings_fastembed.py b/tests/test_embeddings_fastembed.py
index a7ae4f2708..bf6f8a9f54 100644
--- a/tests/test_embeddings_fastembed.py
+++ b/tests/test_embeddings_fastembed.py
@@ -16,12 +16,54 @@
 import os
 
 import pytest
+from onnxruntime.capi.onnxruntime_pybind11_state import NoSuchFile
 
 from nemoguardrails.embeddings.providers.fastembed import FastEmbedEmbeddingModel
 
 LIVE_TEST_MODE = os.environ.get("LIVE_TEST")
 
 
+class _FakeEmbeddingVector:
+    def tolist(self):
+        return [0.1, 0.2]
+
+
+def test_recovers_from_missing_onnxruntime_model_cache(monkeypatch):
+    calls = []
+
+    class FakeTextEmbedding:
+        def __init__(self, model_name, **kwargs):
+            calls.append((model_name, kwargs))
+            if len(calls) == 1:
+                raise NoSuchFile(
+                    "[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /tmp/model.onnx failed. File doesn't exist"
+                )
+
+        def embed(self, documents):
+            return [_FakeEmbeddingVector()]
+
+    monkeypatch.setattr("fastembed.TextEmbedding", FakeTextEmbedding)
+
+    model = FastEmbedEmbeddingModel("all-MiniLM-L6-v2")
+
+    assert model.embedding_size == 2
+    assert calls == [
+        ("sentence-transformers/all-MiniLM-L6-v2", {}),
+        ("sentence-transformers/all-MiniLM-L6-v2", {"cache_dir": ".cache"}),
+    ]
+
+
+def test_reraises_unrelated_fastembed_errors(monkeypatch):
+    class FakeTextEmbedding:
+        def __init__(self, model_name, **kwargs):
+            raise ValueError("unrelated failure")
+
+    monkeypatch.setattr("fastembed.TextEmbedding", FakeTextEmbedding)
+
+    with pytest.raises(ValueError, match="unrelated failure"):
+        FastEmbedEmbeddingModel("all-MiniLM-L6-v2")
+
+
 @pytest.mark.skipif(not LIVE_TEST_MODE, reason="Not in live mode.")
 def test_sync_embeddings():
     model = FastEmbedEmbeddingModel("all-MiniLM-L6-v2")