iPhone 15 Pro
Geekbench AI Score
3527
Single Precision Score
6342
Half Precision Score
5160
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | finnmund |
| Upload Date | February 28 2025 07:52 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| 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% |
1391
258.8 IPS |
|
|
Image Classification (HP)
|
100% |
2633
489.6 IPS |
|
|
Image Classification (Q)
|
96% |
1778
332.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1372
22.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2251
36.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2839
46.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6465
7.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
13155
15.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
12163
14.3 IPS |
|
|
Object Detection (SP)
|
100% |
1626
128.9 IPS |
|
|
Object Detection (HP)
|
97% |
3145
250.3 IPS |
|
|
Object Detection (Q)
|
94% |
2168
172.8 IPS |
|
|
Face Detection (SP)
|
100% |
2978
35.4 IPS |
|
|
Face Detection (HP)
|
100% |
6052
71.9 IPS |
|
|
Face Detection (Q)
|
100% |
3589
42.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6105
47.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
12212
94.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
8421
65.8 IPS |
|
|
Style Transfer (SP)
|
100% |
18490
23.8 IPS |
|
|
Style Transfer (HP)
|
100% |
29488
37.9 IPS |
|
|
Style Transfer (Q)
|
96% |
25247
32.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4272
157.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5604
206.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4062
150.0 IPS |
|
|
Text Classification (SP)
|
100% |
3184
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
5733
7.65 KIPS |
|
|
Text Classification (Q)
|
93% |
5457
7.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
3248
55.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6135
106.0 IPS |
|
|
Machine Translation (Q)
|
98% |
5948
102.8 IPS |
