diff --git a/mobile/lib/services/machine_learning/ml_computer.dart b/mobile/lib/services/machine_learning/ml_computer.dart
index 00044a4b8a..8c370b31d1 100644
--- a/mobile/lib/services/machine_learning/ml_computer.dart
+++ b/mobile/lib/services/machine_learning/ml_computer.dart
@@ -6,6 +6,7 @@ import 'dart:typed_data' show Uint8List;
 import "package:dart_ui_isolate/dart_ui_isolate.dart";
 import "package:logging/logging.dart";
 import "package:photos/face/model/box.dart";
+import "package:photos/services/machine_learning/ml_model.dart";
 import "package:photos/services/machine_learning/semantic_search/clip/clip_text_encoder.dart";
 import "package:photos/services/remote_assets_service.dart";
 import "package:photos/utils/image_ml_util.dart";
@@ -13,6 +14,7 @@ import "package:synchronized/synchronized.dart";
 
 enum MLComputerOperation {
   generateFaceThumbnails,
+  loadModel,
   runClipText,
 }
 
@@ -85,6 +87,15 @@ class MLComputerIsolate {
               faceBoxes,
             );
             sendPort.send(List.from(results));
+          case MLComputerOperation.loadModel:
+            final modelName = args['modelName'] as String;
+            final modelPath = args['modelPath'] as String;
+            final int address = await MlModel.loadModel(
+              modelName,
+              modelPath,
+            );
+            sendPort.send(address);
+            break;
           case MLComputerOperation.runClipText:
             final textEmbedding = await ClipTextEncoder.predict(args);
             sendPort.send(List.from(textEmbedding, growable: false));
@@ -147,10 +158,12 @@ class MLComputerIsolate {
 
   Future<List<double>> runClipText(String query) async {
     try {
+      await _ensureLoadedClipTextModel();
       final int clipAddress = ClipTextEncoder.instance.sessionAddress;
-      final String remotePath = ClipTextEncoder.instance.vocabRemotePath;
+      final String tokenizerRemotePath =
+          ClipTextEncoder.instance.vocabRemotePath;
       final String tokenizerVocabPath =
-          await RemoteAssetsService.instance.getAssetPath(remotePath);
+          await RemoteAssetsService.instance.getAssetPath(tokenizerRemotePath);
       final textEmbedding = await _runInIsolate(
         (
           MLComputerOperation.runClipText,
@@ -168,4 +181,27 @@ class MLComputerIsolate {
       rethrow;
     }
   }
+
+  Future<void> _ensureLoadedClipTextModel() async {
+    try {
+      if (ClipTextEncoder.instance.isInitialized) return;
+      final String modelName = ClipTextEncoder.instance.modelName;
+      final String remotePath = ClipTextEncoder.instance.modelRemotePath;
+      final String modelPath =
+          await RemoteAssetsService.instance.getAssetPath(remotePath);
+      final address = await _runInIsolate(
+        (
+          MLComputerOperation.loadModel,
+          {
+            'modelName': modelName,
+            'modelPath': modelPath,
+          },
+        ),
+      ) as int;
+      ClipTextEncoder.instance.storeSessionAddress(address);
+    } catch (e, s) {
+      _logger.severe("Could not load clip text model in MLComputer", e, s);
+      rethrow;
+    }
+  }
 }