Google volteer
Geekbench AI Score
17
Single Precision Score
17
Half Precision Score
9
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | gethen |
| Upload Date | January 04 2025 02:24 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | placeholder |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google volteer |
| Model ID | Google volteer |
| Motherboard | eldrid |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 6.98 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
3.70 KIPS |
|
|
Image Classification (HP)
|
0% |
0
3.70 KIPS |
|
|
Image Classification (Q)
|
0% |
0
3.71 KIPS |
|
|
Image Segmentation (SP)
|
73% |
22367
386.5 IPS |
|
|
Image Segmentation (HP)
|
73% |
23021
397.8 IPS |
|
|
Image Segmentation (Q)
|
73% |
56971
984.5 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
1.17 KIPS |
|
|
Pose Estimation (HP)
|
0% |
0
1.19 KIPS |
|
|
Pose Estimation (Q)
|
0% |
0
3.32 KIPS |
|
|
Object Detection (SP)
|
0% |
0
1.83 KIPS |
|
|
Object Detection (HP)
|
0% |
0
1.84 KIPS |
|
|
Object Detection (Q)
|
0% |
0
1.39 KIPS |
|
|
Face Detection (SP)
|
0% |
0
610.2 IPS |
|
|
Face Detection (HP)
|
0% |
0
578.5 IPS |
|
|
Face Detection (Q)
|
0% |
0
918.9 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
1.18 KIPS |
|
|
Depth Estimation (HP)
|
0% |
0
1.17 KIPS |
|
|
Depth Estimation (Q)
|
0% |
0
1.10 KIPS |
|
|
Style Transfer (SP)
|
32% |
217734
2.73 KIPS |
|
|
Style Transfer (HP)
|
32% |
216002
2.71 KIPS |
|
|
Style Transfer (Q)
|
0% |
0
5.21 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
2.51 KIPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
2.53 KIPS |
|
|
Image Super-Resolution (Q)
|
2% |
271
3.20 KIPS |
|
|
Text Classification (SP)
|
29% |
522
9.01 KIPS |
|
|
Text Classification (HP)
|
29% |
516
8.91 KIPS |
|
|
Text Classification (Q)
|
29% |
313
5.40 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
11.2 IPS |
|
|
Machine Translation (HP)
|
0% |
0
11.0 IPS |
|
|
Machine Translation (Q)
|
0% |
0
7.95 IPS |
