samsung SM-F741B
Geekbench ML Score
1078
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 07:57 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F741B |
| Model ID | samsung SM-F741B |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
409
76.5 IPS |
|
|
Image Classification (F16)
|
100% |
570
106.6 IPS |
|
|
Image Classification (I8)
|
99% |
422
79.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
962
16.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1311
21.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1305
21.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1036
1.25 IPS |
|
|
Pose Estimation (F16)
|
100% |
2376
2.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
2201
2.67 IPS |
|
|
Object Detection (F32)
|
100% |
319
23.8 IPS |
|
|
Object Detection (F16)
|
100% |
417
31.1 IPS |
|
|
Object Detection (I8)
|
62% |
369
27.6 IPS |
|
|
Face Detection (F32)
|
100% |
2061
24.5 IPS |
|
|
Face Detection (F16)
|
97% |
1753
20.8 IPS |
|
|
Face Detection (I8)
|
86% |
2174
25.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1365
10.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2815
21.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2858
22.2 IPS |
|
|
Style Transfer (F32)
|
100% |
4247
5.59 IPS |
|
|
Style Transfer (F16)
|
100% |
8007
10.5 IPS |
|
|
Style Transfer (I8)
|
98% |
7959
10.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
333
11.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
773
27.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
721
25.7 IPS |
|
|
Text Classification (F32)
|
100% |
440
632.9 IPS |
|
|
Text Classification (F16)
|
100% |
436
626.8 IPS |
|
|
Text Classification (I8)
|
92% |
710
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
711
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
682
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
784
14.4 IPS |
