Google Pixel 9a
Geekbench AI Score
1092
Single Precision Score
1840
Half Precision Score
1468
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | tocophonic |
| Upload Date | December 07 2025 10:08 PM |
| Views | 7 |
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 | 7.39 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
754
140.2 IPS |
|
|
Image Classification (HP)
|
100% |
1093
203.2 IPS |
|
|
Image Classification (Q)
|
97% |
1113
207.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1634
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2657
43.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2446
39.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5365
6.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
13117
15.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
12593
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
626
49.7 IPS |
|
|
Object Detection (HP)
|
99% |
1069
84.8 IPS |
|
|
Object Detection (Q)
|
83% |
1068
86.2 IPS |
|
|
Face Detection (SP)
|
100% |
2772
32.9 IPS |
|
|
Face Detection (HP)
|
100% |
3358
39.9 IPS |
|
|
Face Detection (Q)
|
96% |
3102
37.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3634
28.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
5940
45.9 IPS |
|
|
Depth Estimation (Q)
|
62% |
4950
47.0 IPS |
|
|
Style Transfer (SP)
|
100% |
8062
10.4 IPS |
|
|
Style Transfer (HP)
|
100% |
21264
27.3 IPS |
|
|
Style Transfer (Q)
|
98% |
20213
26.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1902
70.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2415
89.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2296
85.1 IPS |
|
|
Text Classification (SP)
|
35% |
11
96.6 IPS |
|
|
Text Classification (HP)
|
35% |
27
248.2 IPS |
|
|
Text Classification (Q)
|
32% |
21
269.2 IPS |
|
|
Machine Translation (SP)
|
100% |
344
5.92 IPS |
|
|
Machine Translation (HP)
|
100% |
397
6.84 IPS |
|
|
Machine Translation (Q)
|
43% |
85
4.94 IPS |
