Zebra Technologies TC58
Geekbench AI Score
327
Single Precision Score
327
Half Precision Score
697
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | kitty_purry |
| Upload Date | April 15 2025 11:31 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Zebra Technologies TC58 |
| Model ID | Zebra Technologies TC58 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.71 GHz |
| Memory Information | |
|---|---|
| Size | 7.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
164
30.5 IPS |
|
|
Image Classification (HP)
|
100% |
164
30.4 IPS |
|
|
Image Classification (Q)
|
100% |
499
92.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
171
2.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
172
2.79 IPS |
|
|
Image Segmentation (Q)
|
98% |
517
8.40 IPS |
|
|
Pose Estimation (SP)
|
100% |
670
0.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
672
0.78 IPS |
|
|
Pose Estimation (Q)
|
84% |
1175
1.39 IPS |
|
|
Object Detection (SP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (HP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (Q)
|
83% |
503
40.6 IPS |
|
|
Face Detection (SP)
|
100% |
368
4.38 IPS |
|
|
Face Detection (HP)
|
100% |
368
4.37 IPS |
|
|
Face Detection (Q)
|
95% |
921
11.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
516
3.98 IPS |
|
|
Depth Estimation (HP)
|
99% |
519
4.00 IPS |
|
|
Depth Estimation (Q)
|
64% |
1102
10.1 IPS |
|
|
Style Transfer (SP)
|
89% |
1198
1.56 IPS |
|
|
Style Transfer (HP)
|
89% |
1210
1.57 IPS |
|
|
Style Transfer (Q)
|
98% |
2488
3.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
294
10.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
294
10.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
662
24.5 IPS |
|
|
Text Classification (SP)
|
100% |
194
259.2 IPS |
|
|
Text Classification (HP)
|
100% |
193
257.8 IPS |
|
|
Text Classification (Q)
|
88% |
381
513.3 IPS |
|
|
Machine Translation (SP)
|
100% |
365
6.28 IPS |
|
|
Machine Translation (HP)
|
100% |
363
6.25 IPS |
|
|
Machine Translation (Q)
|
50% |
281
9.97 IPS |
