Samsung Galaxy Note20 5G
Geekbench ML Score
553
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | saiht |
| Upload Date | July 25 2024 01:01 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Note20 5G |
| Model ID | samsung SM-N981N |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.09 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
260
48.7 IPS |
|
|
Image Classification (F16)
|
100% |
250
46.8 IPS |
|
|
Image Classification (I8)
|
97% |
578
108.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
352
5.88 IPS |
|
|
Image Segmentation (F16)
|
100% |
357
5.96 IPS |
|
|
Image Segmentation (I8)
|
98% |
440
7.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
568
0.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
560
0.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
2622
3.18 IPS |
|
|
Object Detection (F32)
|
100% |
272
20.3 IPS |
|
|
Object Detection (F16)
|
100% |
285
21.3 IPS |
|
|
Object Detection (I8)
|
61% |
752
56.2 IPS |
|
|
Face Detection (F32)
|
100% |
612
7.28 IPS |
|
|
Face Detection (F16)
|
100% |
609
7.24 IPS |
|
|
Face Detection (I8)
|
86% |
1484
17.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
560
4.34 IPS |
|
|
Depth Estimation (F16)
|
100% |
525
4.08 IPS |
|
|
Depth Estimation (I8)
|
95% |
1291
10.0 IPS |
|
|
Style Transfer (F32)
|
100% |
930
1.22 IPS |
|
|
Style Transfer (F16)
|
100% |
934
1.23 IPS |
|
|
Style Transfer (I8)
|
98% |
2708
3.56 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
340
12.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
349
12.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1250
44.6 IPS |
|
|
Text Classification (F32)
|
100% |
293
420.7 IPS |
|
|
Text Classification (F16)
|
100% |
303
435.2 IPS |
|
|
Text Classification (I8)
|
92% |
257
369.5 IPS |
|
|
Machine Translation (F32)
|
100% |
616
11.3 IPS |
|
|
Machine Translation (F16)
|
100% |
622
11.5 IPS |
|
|
Machine Translation (I8)
|
64% |
303
5.58 IPS |
