diff --git a/frigate/config/config.py b/frigate/config/config.py
index 6ec048acd..2dc9585ae 100644
--- a/frigate/config/config.py
+++ b/frigate/config/config.py
@@ -506,7 +506,9 @@ class FrigateConfig(FrigateBaseModel):
                 model_config["path"] = detector_config.model_path
 
             if "path" not in model_config:
-                if detector_config.type == "cpu":
+                if detector_config.type == "cpu" or detector_config.type.endswith(
+                    "_tfl"
+                ):
                     model_config["path"] = "/cpu_model.tflite"
                 elif detector_config.type == "edgetpu":
                     model_config["path"] = "/edgetpu_model.tflite"
diff --git a/frigate/detectors/detector_utils.py b/frigate/detectors/detector_utils.py
index d6445d5c0..d732de871 100644
--- a/frigate/detectors/detector_utils.py
+++ b/frigate/detectors/detector_utils.py
@@ -1,5 +1,16 @@
+import logging
+import os
+
 import numpy as np
 
+try:
+    from tflite_runtime.interpreter import Interpreter, load_delegate
+except ModuleNotFoundError:
+    from tensorflow.lite.python.interpreter import Interpreter, load_delegate
+
+
+logger = logging.getLogger(__name__)
+
 
 def tflite_init(self, interpreter):
     self.interpreter = interpreter
@@ -34,3 +45,30 @@ def tflite_detect_raw(self, tensor_input):
         ]
 
     return detections
+
+
+def tflite_load_delegate_interpreter(
+    delegate_library: str, detector_config, device_config
+):
+    try:
+        logger.info("Attempting to load NPU")
+        tf_delegate = load_delegate(delegate_library, device_config)
+        logger.info("NPU found")
+        interpreter = Interpreter(
+            model_path=detector_config.model.path,
+            experimental_delegates=[tf_delegate],
+        )
+        return interpreter
+    except ValueError:
+        _, ext = os.path.splitext(detector_config.model.path)
+
+        if ext and ext != ".tflite":
+            logger.error(
+                "Incorrect model used with NPU. Only .tflite models can be used with a TFLite delegate."
+            )
+        else:
+            logger.error(
+                "No NPU was detected. If you do not have a TFLite device yet, you must configure CPU detectors."
+            )
+
+        raise
diff --git a/frigate/detectors/plugins/teflon_tfl.py b/frigate/detectors/plugins/teflon_tfl.py
new file mode 100644
index 000000000..7e29d6630
--- /dev/null
+++ b/frigate/detectors/plugins/teflon_tfl.py
@@ -0,0 +1,38 @@
+import logging
+
+from typing_extensions import Literal
+
+from frigate.detectors.detection_api import DetectionApi
+from frigate.detectors.detector_config import BaseDetectorConfig
+
+from ..detector_utils import (
+    tflite_detect_raw,
+    tflite_init,
+    tflite_load_delegate_interpreter,
+)
+
+logger = logging.getLogger(__name__)
+
+# Use _tfl suffix to default tflite model
+DETECTOR_KEY = "teflon_tfl"
+
+
+class TeflonDetectorConfig(BaseDetectorConfig):
+    type: Literal[DETECTOR_KEY]
+
+
+class TeflonTfl(DetectionApi):
+    type_key = DETECTOR_KEY
+
+    def __init__(self, detector_config: TeflonDetectorConfig):
+        # Location in Debian's mesa-teflon-delegate
+        delegate_library = "/usr/lib/teflon/libteflon.so"
+        device_config = {}
+
+        interpreter = tflite_load_delegate_interpreter(
+            delegate_library, detector_config, device_config
+        )
+        tflite_init(self, interpreter)
+
+    def detect_raw(self, tensor_input):
+        return tflite_detect_raw(self, tensor_input)