samsung SM-S921Q
Geekbench ML Score
1217
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 08:07 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S921Q |
| Model ID | samsung SM-S921Q |
| 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 | 6.93 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
543
101.5 IPS |
|
|
Image Classification (F16)
|
100% |
561
105.0 IPS |
|
|
Image Classification (I8)
|
97% |
998
186.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
795
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
791
13.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
966
16.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1394
1.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
1320
1.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
5857
7.09 IPS |
|
|
Object Detection (F32)
|
100% |
575
43.0 IPS |
|
|
Object Detection (F16)
|
100% |
606
45.2 IPS |
|
|
Object Detection (I8)
|
61% |
1365
101.9 IPS |
|
|
Face Detection (F32)
|
100% |
1260
15.0 IPS |
|
|
Face Detection (F16)
|
100% |
1333
15.9 IPS |
|
|
Face Detection (I8)
|
86% |
2369
28.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1348
10.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1299
10.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2624
20.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2362
3.11 IPS |
|
|
Style Transfer (F16)
|
100% |
2313
3.04 IPS |
|
|
Style Transfer (I8)
|
98% |
5038
6.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
913
32.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
960
34.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2810
100.4 IPS |
|
|
Text Classification (F32)
|
100% |
709
1.02 KIPS |
|
|
Text Classification (F16)
|
100% |
722
1.04 KIPS |
|
|
Text Classification (I8)
|
92% |
537
772.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1415
26.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1361
25.1 IPS |
|
|
Machine Translation (I8)
|
64% |
593
10.9 IPS |
