motorola motorola razr 60 ultra
Geekbench AI Score
1607
Single Precision Score
2169
Half Precision Score
2639
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | saulmaz |
| Upload Date | March 17 2026 07:00 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola motorola razr 60 ultra |
| Model ID | motorola motorola razr 60 ultra |
| Motherboard | leap |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 14.82 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
984
182.9 IPS |
|
|
Image Classification (HP)
|
100% |
1163
216.4 IPS |
|
|
Image Classification (Q)
|
99% |
2106
392.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1275
20.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1556
25.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2338
38.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3052
3.56 IPS |
|
|
Pose Estimation (HP)
|
92% |
6036
7.09 IPS |
|
|
Pose Estimation (Q)
|
96% |
7656
8.97 IPS |
|
|
Object Detection (SP)
|
98% |
983
78.3 IPS |
|
|
Object Detection (HP)
|
97% |
1152
91.7 IPS |
|
|
Object Detection (Q)
|
85% |
1853
149.3 IPS |
|
|
Face Detection (SP)
|
100% |
2783
33.1 IPS |
|
|
Face Detection (HP)
|
100% |
3790
45.0 IPS |
|
|
Face Detection (Q)
|
97% |
4953
59.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
2592
20.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
4444
34.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
5623
51.9 IPS |
|
|
Style Transfer (SP)
|
89% |
6557
8.51 IPS |
|
|
Style Transfer (HP)
|
88% |
7409
9.62 IPS |
|
|
Style Transfer (Q)
|
98% |
12987
16.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1350
49.8 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
2632
97.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3033
112.4 IPS |
|
|
Text Classification (SP)
|
100% |
523
697.7 IPS |
|
|
Text Classification (HP)
|
100% |
592
790.4 IPS |
|
|
Text Classification (Q)
|
93% |
432
580.4 IPS |
|
|
Machine Translation (SP)
|
100% |
916
15.8 IPS |
|
|
Machine Translation (HP)
|
96% |
943
16.3 IPS |
|
|
Machine Translation (Q)
|
55% |
496
13.3 IPS |
