diff --git a/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_postprocessing.dart b/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_postprocessing.dart
index 417b99e8e4..a01017559d 100644
--- a/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_postprocessing.dart
+++ b/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_postprocessing.dart
@@ -1,4 +1,3 @@
-import 'dart:developer' as dev show log;
 import 'dart:math' as math show max, min;
 
 import 'package:photos/services/machine_learning/face_ml/face_detection/detection.dart';
@@ -33,9 +32,6 @@ List<FaceDetectionRelative> yoloOnnxFilterExtractDetections(
         maxScore = result[4];
       }
     }
-    dev.log(
-      'No face detections found above the minScoreSigmoidThreshold of $minScoreSigmoidThreshold. The max score was $maxScore.',
-    );
   }
 
   for (final List<double> rawDetection in output) {
diff --git a/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_service.dart b/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_service.dart
index 728de95dae..7622b011d8 100644
--- a/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_service.dart
+++ b/mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_service.dart
@@ -66,9 +66,8 @@ class FaceDetectionService extends MlModel {
       maintainAspectRatio: true,
     );
     final preprocessingTime = DateTime.now();
-    _logger.info(
-      'Face detection preprocessing is finished, in ${preprocessingTime.difference(startTime).inMilliseconds} ms',
-    );
+    final preprocessingMs =
+        preprocessingTime.difference(startTime).inMilliseconds;
 
     // Run inference
     List<List<List<double>>>? nestedResults = [];
@@ -81,11 +80,14 @@ class FaceDetectionService extends MlModel {
           inputImageList,
         ); // [1, 25200, 16]
       }
+      final inferenceTime = DateTime.now();
+      final inferenceMs =
+          inferenceTime.difference(preprocessingTime).inMilliseconds;
       _logger.info(
-        'inference is finished, in ${DateTime.now().difference(preprocessingTime).inMilliseconds} ms',
+        'Face detection is finished, in ${inferenceTime.difference(startTime).inMilliseconds} ms (preprocessing: $preprocessingMs ms, inference: $inferenceMs ms)',
       );
     } catch (e, s) {
-      _logger.severe('Error while running inference', e, s);
+      _logger.severe('Error while running inference (PlatformPlugin: ${MlModel.usePlatformPlugin})', e, s);
       throw YOLOFaceInterpreterRunException();
     }
     try {
@@ -121,9 +123,9 @@ class FaceDetectionService extends MlModel {
         outputs[0]?.value as List<List<List<double>>>; // [1, 25200, 16]
     inputOrt.release();
     runOptions.release();
-    outputs.forEach((element) {
+    for (var element in outputs) {
       element?.release();
-    });
+    }
 
     return result;
   }
diff --git a/mobile/lib/services/machine_learning/ml_indexing_isolate.dart b/mobile/lib/services/machine_learning/ml_indexing_isolate.dart
index 6a0d26b45b..91dae6906b 100644
--- a/mobile/lib/services/machine_learning/ml_indexing_isolate.dart
+++ b/mobile/lib/services/machine_learning/ml_indexing_isolate.dart
@@ -51,7 +51,6 @@ class MLIndexingIsolate extends SuperIsolate {
     FileMLInstruction instruction,
     String filePath,
   ) async {
-    final Stopwatch stopwatch = Stopwatch()..start();
     late MLResult result;
 
     try {
@@ -79,15 +78,10 @@ class MLIndexingIsolate extends SuperIsolate {
         s,
       );
       debugPrint(
-        "This image with ID ${instruction.file.uploadedFileID} has name ${instruction.file.displayName}.",
+        "This image with fileID ${instruction.file.uploadedFileID} has name ${instruction.file.displayName}.",
       );
       rethrow;
     }
-    stopwatch.stop();
-    _logger.info(
-      "Finished Analyze image with uploadedFileID ${instruction.file.uploadedFileID}, in "
-      "${stopwatch.elapsedMilliseconds} ms (including time waiting for inference engine availability)",
-    );
 
     return result;
   }
diff --git a/mobile/lib/services/machine_learning/ml_service.dart b/mobile/lib/services/machine_learning/ml_service.dart
index 19ef46f2be..55ce37d37a 100644
--- a/mobile/lib/services/machine_learning/ml_service.dart
+++ b/mobile/lib/services/machine_learning/ml_service.dart
@@ -385,9 +385,6 @@ class MLService {
   }
 
   Future<bool> processImage(FileMLInstruction instruction) async {
-    _logger.info(
-      "`processImage` start processing image with uploadedFileID: ${instruction.file.uploadedFileID}",
-    );
     bool actuallyRanML = false;
 
     try {
@@ -420,7 +417,6 @@ class MLService {
       if (result.facesRan) {
         if (result.faces!.isEmpty) {
           faces.add(Face.empty(result.fileId));
-          _logger.info("no face detected, storing empty for ${result.fileId}");
         }
         if (result.faces!.isNotEmpty) {
           for (int i = 0; i < result.faces!.length; ++i) {
@@ -432,7 +428,6 @@ class MLService {
               ),
             );
           }
-          _logger.info("storing ${faces.length} faces for ${result.fileId}");
         }
         dataEntity.putFace(
           RemoteFaceEmbedding(
@@ -459,7 +454,7 @@ class MLService {
         instruction.file,
         dataEntity,
       );
-      _logger.info("Results for file ${result.fileId} stored on remote");
+      _logger.info("ML results for fileID ${result.fileId} stored on remote");
       // Storing results locally
       if (result.facesRan) await MLDataDB.instance.bulkInsertFaces(faces);
       if (result.clipRan) {
@@ -467,7 +462,7 @@ class MLService {
           result.clip!,
         );
       }
-      _logger.info("Results for file ${result.fileId} stored locally");
+      _logger.info("ML results for fileID ${result.fileId} stored locally");
       return actuallyRanML;
     } catch (e, s) {
       final String errorString = e.toString();
@@ -480,7 +475,7 @@ class MLService {
               errorString.contains('FileSizeTooLargeForMobileIndexing');
       if (acceptedIssue) {
         _logger.severe(
-          '$errorString with ID ${instruction.file.uploadedFileID} (format $format, type $fileType, size $size), storing empty results so indexing does not get stuck',
+          '$errorString for fileID ${instruction.file.uploadedFileID} (format $format, type $fileType, size $size), storing empty results so indexing does not get stuck',
           e,
           s,
         );
@@ -493,7 +488,7 @@ class MLService {
         return true;
       }
       _logger.severe(
-        "Failed to index file with ID: ${instruction.file.uploadedFileID} (format $format, type $fileType, size $size). Not storing any results locally, which means it will be automatically retried later.",
+        "Failed to index file for fileID ${instruction.file.uploadedFileID} (format $format, type $fileType, size $size). Not storing any results locally, which means it will be automatically retried later.",
         e,
         s,
       );
diff --git a/mobile/lib/services/machine_learning/semantic_search/clip/clip_image_encoder.dart b/mobile/lib/services/machine_learning/semantic_search/clip/clip_image_encoder.dart
index 193e9bac14..24dd7e7bba 100644
--- a/mobile/lib/services/machine_learning/semantic_search/clip/clip_image_encoder.dart
+++ b/mobile/lib/services/machine_learning/semantic_search/clip/clip_image_encoder.dart
@@ -40,16 +40,25 @@ class ClipImageEncoder extends MlModel {
     final preprocessingMs =
         preprocessingTime.difference(startTime).inMilliseconds;
     late List<double> result;
-    if (MlModel.usePlatformPlugin) {
-      result = await _runPlatformPluginPredict(inputList);
-    } else {
-      result = _runFFIBasedPredict(inputList, sessionAddress);
+    try {
+      if (MlModel.usePlatformPlugin) {
+        result = await _runPlatformPluginPredict(inputList);
+      } else {
+        result = _runFFIBasedPredict(inputList, sessionAddress);
+      }
+    } catch (e, stackTrace) {
+      _logger.severe(
+        "Clip image inference failed${enteFileID != null ? " with fileID $enteFileID" : ""}  (PlatformPlugin: ${MlModel.usePlatformPlugin})",
+        e,
+        stackTrace,
+      );
+      rethrow;
     }
     final inferTime = DateTime.now();
     final inferenceMs = inferTime.difference(preprocessingTime).inMilliseconds;
     final totalMs = inferTime.difference(startTime).inMilliseconds;
     _logger.info(
-      "Clip predict took $totalMs ms${enteFileID != null ? " with fileID $enteFileID" : ""} (nference: $inferenceMs ms, preprocessing: $preprocessingMs ms)",
+      "Clip image predict took $totalMs ms${enteFileID != null ? " with fileID $enteFileID" : ""} (inference: $inferenceMs ms, preprocessing: $preprocessingMs ms)",
     );
     return result;
   }
diff --git a/mobile/lib/services/machine_learning/semantic_search/clip/clip_text_encoder.dart b/mobile/lib/services/machine_learning/semantic_search/clip/clip_text_encoder.dart
index cd59fd1aa5..8a50b785f1 100644
--- a/mobile/lib/services/machine_learning/semantic_search/clip/clip_text_encoder.dart
+++ b/mobile/lib/services/machine_learning/semantic_search/clip/clip_text_encoder.dart
@@ -36,10 +36,19 @@ class ClipTextEncoder extends MlModel {
     final address = args["address"] as int;
     final List<int> tokenize = await ClipTextTokenizer.instance.tokenize(text);
     final int32list = Int32List.fromList(tokenize);
-    if (MlModel.usePlatformPlugin) {
-      return await _runPlatformPluginPredict(int32list);
-    } else {
-      return _runFFIBasedPredict(int32list, address);
+    try {
+      if (MlModel.usePlatformPlugin) {
+        return await _runPlatformPluginPredict(int32list);
+      } else {
+        return _runFFIBasedPredict(int32list, address);
+      }
+    } catch (e, s) {
+      _logger.severe(
+        "Clip text inference failed  (PlatformPlugin: ${MlModel.usePlatformPlugin})",
+        e,
+        s,
+      );
+      rethrow;
     }
   }
 
diff --git a/mobile/lib/utils/image_ml_util.dart b/mobile/lib/utils/image_ml_util.dart
index 0de42f0c98..9b68ca9b3a 100644
--- a/mobile/lib/utils/image_ml_util.dart
+++ b/mobile/lib/utils/image_ml_util.dart
@@ -259,7 +259,6 @@ Future<(Float32List, List<AlignmentResult>, List<bool>, List<double>, Size)>
   int width = 112,
   int height = 112,
 }) async {
-  final stopwatch = Stopwatch()..start();
 
   final Size originalSize =
       Size(image.width.toDouble(), image.height.toDouble());
@@ -299,31 +298,20 @@ Future<(Float32List, List<AlignmentResult>, List<bool>, List<double>, Size)>
       alignedImageIndex,
     );
 
-    final blurDetectionStopwatch = Stopwatch()..start();
     final faceGrayMatrix = _createGrayscaleIntMatrixFromNormalized2List(
       alignedImagesFloat32List,
       alignedImageIndex,
     );
 
     alignedImageIndex += 3 * width * height;
-    final grayscalems = blurDetectionStopwatch.elapsedMilliseconds;
-    log('creating grayscale matrix took $grayscalems ms');
     final (isBlur, blurValue) =
         await BlurDetectionService.predictIsBlurGrayLaplacian(
       faceGrayMatrix,
       faceDirection: face.getFaceDirection(),
     );
-    final blurms = blurDetectionStopwatch.elapsedMilliseconds - grayscalems;
-    log('blur detection took $blurms ms');
-    log(
-      'total blur detection took ${blurDetectionStopwatch.elapsedMilliseconds} ms',
-    );
-    blurDetectionStopwatch.stop();
     isBlurs.add(isBlur);
     blurValues.add(blurValue);
   }
-  stopwatch.stop();
-  log("Face Alignment took: ${stopwatch.elapsedMilliseconds} ms");
   return (
     alignedImagesFloat32List,
     alignmentResults,
diff --git a/mobile/lib/utils/ml_util.dart b/mobile/lib/utils/ml_util.dart
index 817c0bd4ea..d43a3ef7d3 100644
--- a/mobile/lib/utils/ml_util.dart
+++ b/mobile/lib/utils/ml_util.dart
@@ -332,7 +332,7 @@ Future<String> getImagePathForML(EnteFile enteFile) async {
   imagePath = file?.path;
   stopwatch.stop();
   _logger.info(
-    "Getting file data for uploadedFileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
+    "Getting file data for fileID ${enteFile.uploadedFileID} took ${stopwatch.elapsedMilliseconds} ms",
   );
 
   if (imagePath == null) {
@@ -388,7 +388,7 @@ Future<MLResult> analyzeImageStatic(Map args) async {
     final int clipImageAddress = args["clipImageAddress"] as int;
 
     _logger.info(
-      "Start analyzeImageStatic with fileID: $enteFileID (runFaces: $runFaces, runClip: $runClip)",
+      "Start analyzeImageStatic for fileID $enteFileID (runFaces: $runFaces, runClip: $runClip)",
     );
     final startTime = DateTime.now();
 
@@ -399,9 +399,7 @@ Future<MLResult> analyzeImageStatic(Map args) async {
     final result = MLResult.fromEnteFileID(enteFileID);
     result.decodedImageSize = decodedImageSize;
     final decodeTime = DateTime.now();
-    _logger.info(
-      'Reading and decoding image took ${decodeTime.difference(startTime).inMilliseconds} ms (fileID: $enteFileID)',
-    );
+    final decodeMs = decodeTime.difference(startTime).inMilliseconds;
 
     if (runFaces) {
       final resultFaces = await FaceRecognitionService.runFacesPipeline(
@@ -417,6 +415,9 @@ Future<MLResult> analyzeImageStatic(Map args) async {
         result.faces = resultFaces;
       }
     }
+    final facesTime = DateTime.now();
+    final facesMs = facesTime.difference(decodeTime).inMilliseconds;
+    final faceMsString = runFaces ? ", faces: $facesMs ms" : "";
 
     if (runClip) {
       final clipResult = await SemanticSearchService.runClipImage(
@@ -427,10 +428,14 @@ Future<MLResult> analyzeImageStatic(Map args) async {
       );
       result.clip = clipResult;
     }
+    final clipTime = DateTime.now();
+    final clipMs = clipTime.difference(facesTime).inMilliseconds;
+    final clipMsString = runClip ? ", clip: $clipMs ms" : "";
 
     final endTime = DateTime.now();
+    final totalMs = endTime.difference(startTime).inMilliseconds;
     _logger.info(
-      'Finished analyzeImageStatic with fileID: $enteFileID, in ${endTime.difference(startTime).inMilliseconds} ms',
+      'Finished analyzeImageStatic for fileID $enteFileID, in $totalMs ms (decode: $decodeMs ms$faceMsString$clipMsString)',
     );
 
     return result;