OPPO CPH2689
Geekbench AI Score
966
Single Precision Score
1210
Half Precision Score
945
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 21 2026 10:17 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO CPH2689 |
| Model ID | OPPO CPH2689 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
480
89.2 IPS |
|
|
Image Classification (HP)
|
100% |
501
93.2 IPS |
|
|
Image Classification (Q)
|
97% |
401
74.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1608
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2414
39.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1940
31.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6684
7.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
11994
14.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
9908
11.6 IPS |
|
|
Object Detection (SP)
|
100% |
396
31.4 IPS |
|
|
Object Detection (HP)
|
99% |
567
45.0 IPS |
|
|
Object Detection (Q)
|
83% |
515
41.6 IPS |
|
|
Face Detection (SP)
|
100% |
2274
27.0 IPS |
|
|
Face Detection (HP)
|
100% |
2447
29.1 IPS |
|
|
Face Detection (Q)
|
96% |
2536
30.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
2962
22.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
4522
34.9 IPS |
|
|
Depth Estimation (Q)
|
62% |
2990
28.4 IPS |
|
|
Style Transfer (SP)
|
100% |
10935
14.1 IPS |
|
|
Style Transfer (HP)
|
100% |
16416
21.1 IPS |
|
|
Style Transfer (Q)
|
98% |
15120
19.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1152
42.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1431
52.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1329
49.3 IPS |
|
|
Text Classification (SP)
|
35% |
13
121.3 IPS |
|
|
Text Classification (HP)
|
29% |
9
149.4 IPS |
|
|
Text Classification (Q)
|
32% |
11
142.5 IPS |
|
|
Machine Translation (SP)
|
100% |
317
5.46 IPS |
|
|
Machine Translation (HP)
|
100% |
351
6.05 IPS |
|
|
Machine Translation (Q)
|
43% |
86
5.01 IPS |
