Google Pixel 9a
Geekbench AI Score
1120
Single Precision Score
1717
Half Precision Score
1296
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | markerichannelly |
| Upload Date | September 01 2025 04:27 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Google Pixel 9a |
| Model ID | Google Pixel 9a |
| Motherboard | tegu |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 7.38 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
667
124.1 IPS |
|
|
Image Classification (HP)
|
100% |
702
130.6 IPS |
|
|
Image Classification (Q)
|
97% |
505
94.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1567
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2249
36.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1818
29.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5345
6.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
13878
16.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
13158
15.4 IPS |
|
|
Object Detection (SP)
|
100% |
594
47.2 IPS |
|
|
Object Detection (HP)
|
99% |
1015
80.5 IPS |
|
|
Object Detection (Q)
|
83% |
1057
85.3 IPS |
|
|
Face Detection (SP)
|
100% |
2744
32.6 IPS |
|
|
Face Detection (HP)
|
100% |
3345
39.7 IPS |
|
|
Face Detection (Q)
|
96% |
2975
35.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
3674
28.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
6251
48.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
4875
46.3 IPS |
|
|
Style Transfer (SP)
|
100% |
8114
10.4 IPS |
|
|
Style Transfer (HP)
|
100% |
21672
27.9 IPS |
|
|
Style Transfer (Q)
|
98% |
20376
26.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1943
71.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2478
91.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2301
85.3 IPS |
|
|
Text Classification (SP)
|
35% |
22
202.7 IPS |
|
|
Text Classification (HP)
|
35% |
26
232.6 IPS |
|
|
Text Classification (Q)
|
32% |
20
255.9 IPS |
|
|
Machine Translation (SP)
|
100% |
269
4.64 IPS |
|
|
Machine Translation (HP)
|
100% |
344
5.92 IPS |
|
|
Machine Translation (Q)
|
43% |
77
4.47 IPS |
