Google Pixel 7a
Geekbench AI Score
738
Single Precision Score
1047
Half Precision Score
840
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | SHUBHAMSARAF |
| Upload Date | September 29 2025 10:09 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Google Tensor G2 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Google Pixel 7a |
| Model ID | Google Pixel 7a |
| Motherboard | lynx |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.35 GHz |
| Cluster 3 | 2 Cores @ 2.85 GHz |
| Memory Information | |
|---|---|
| Size | 7.27 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
288
53.5 IPS |
|
|
Image Classification (HP)
|
100% |
295
54.9 IPS |
|
|
Image Classification (Q)
|
97% |
294
54.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1122
18.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1494
24.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1277
20.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4359
5.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
9614
11.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
9328
10.9 IPS |
|
|
Object Detection (SP)
|
100% |
377
29.9 IPS |
|
|
Object Detection (HP)
|
99% |
479
38.0 IPS |
|
|
Object Detection (Q)
|
83% |
445
35.9 IPS |
|
|
Face Detection (SP)
|
100% |
1714
20.4 IPS |
|
|
Face Detection (HP)
|
100% |
2387
28.4 IPS |
|
|
Face Detection (Q)
|
96% |
2269
27.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2289
17.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
3755
29.0 IPS |
|
|
Depth Estimation (Q)
|
62% |
2986
28.4 IPS |
|
|
Style Transfer (SP)
|
100% |
6418
8.25 IPS |
|
|
Style Transfer (HP)
|
100% |
15346
19.7 IPS |
|
|
Style Transfer (Q)
|
98% |
16207
20.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1083
40.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1218
45.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1217
45.1 IPS |
|
|
Text Classification (SP)
|
35% |
12
109.9 IPS |
|
|
Text Classification (HP)
|
35% |
16
145.6 IPS |
|
|
Text Classification (Q)
|
32% |
11
147.8 IPS |
|
|
Machine Translation (SP)
|
100% |
277
4.78 IPS |
|
|
Machine Translation (HP)
|
100% |
292
5.03 IPS |
|
|
Machine Translation (Q)
|
43% |
77
4.46 IPS |
