diff --git a/frigate/data_processing/common/audio_transcription/model.py b/frigate/data_processing/common/audio_transcription/model.py
index 0fe5ddb5c..82472ad62 100644
--- a/frigate/data_processing/common/audio_transcription/model.py
+++ b/frigate/data_processing/common/audio_transcription/model.py
@@ -4,7 +4,6 @@ import logging
 import os
 
 import sherpa_onnx
-from faster_whisper.utils import download_model
 
 from frigate.comms.inter_process import InterProcessRequestor
 from frigate.const import MODEL_CACHE_DIR
@@ -25,6 +24,9 @@ class AudioTranscriptionModelRunner:
 
         if model_size == "large":
             # use the Whisper download function instead of our own
+            # Import dynamically to avoid crashes on systems without AVX support
+            from faster_whisper.utils import download_model
+
             logger.debug("Downloading Whisper audio transcription model")
             download_model(
                 size_or_id="small" if device == "cuda" else "tiny",
diff --git a/frigate/data_processing/post/audio_transcription.py b/frigate/data_processing/post/audio_transcription.py
index 066287707..870c34068 100644
--- a/frigate/data_processing/post/audio_transcription.py
+++ b/frigate/data_processing/post/audio_transcription.py
@@ -6,7 +6,6 @@ import threading
 import time
 from typing import Optional
 
-from faster_whisper import WhisperModel
 from peewee import DoesNotExist
 
 from frigate.comms.inter_process import InterProcessRequestor
@@ -51,6 +50,9 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
 
     def __build_recognizer(self) -> None:
         try:
+            # Import dynamically to avoid crashes on systems without AVX support
+            from faster_whisper import WhisperModel
+
             self.recognizer = WhisperModel(
                 model_size_or_path="small",
                 device="cuda"