iPhone 15 Pro
Geekbench AI Score
3652
Single Precision Score
24825
Half Precision Score
35100
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | November 21 2024 01:14 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1593
296.2 IPS |
|
|
Image Classification (HP)
|
100% |
11422
2.12 KIPS |
|
|
Image Classification (Q)
|
97% |
15518
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1598
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
15538
251.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20508
332.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
6483
7.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
100221
116.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
203235
238.2 IPS |
|
|
Object Detection (SP)
|
100% |
1662
131.8 IPS |
|
|
Object Detection (HP)
|
100% |
13950
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
19140
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
2921
34.7 IPS |
|
|
Face Detection (HP)
|
100% |
34026
404.3 IPS |
|
|
Face Detection (Q)
|
100% |
50933
605.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6443
49.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
77344
595.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
126980
992.8 IPS |
|
|
Style Transfer (SP)
|
100% |
18456
23.7 IPS |
|
|
Style Transfer (HP)
|
100% |
198900
255.7 IPS |
|
|
Style Transfer (Q)
|
96% |
251721
324.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4341
160.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33862
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55648
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3252
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
3308
4.42 KIPS |
|
|
Text Classification (Q)
|
93% |
3411
4.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
3144
54.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6111
105.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7420
128.2 IPS |
