iPhone 15 Pro
Geekbench AI Score
5038
Single Precision Score
5850
Half Precision Score
5646
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | December 13 2025 08:46 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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% |
1981
368.4 IPS |
|
|
Image Classification (HP)
|
100% |
1733
322.2 IPS |
|
|
Image Classification (Q)
|
96% |
1994
372.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3708
60.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
4228
68.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
4079
66.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
13097
15.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
15029
17.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
14531
17.0 IPS |
|
|
Object Detection (SP)
|
100% |
2361
187.3 IPS |
|
|
Object Detection (HP)
|
100% |
2636
209.1 IPS |
|
|
Object Detection (Q)
|
92% |
2499
199.5 IPS |
|
|
Face Detection (SP)
|
100% |
6417
76.2 IPS |
|
|
Face Detection (HP)
|
100% |
8658
102.9 IPS |
|
|
Face Detection (Q)
|
100% |
7129
84.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
11000
84.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
12158
93.7 IPS |
|
|
Depth Estimation (Q)
|
86% |
11402
89.1 IPS |
|
|
Style Transfer (SP)
|
100% |
27036
34.8 IPS |
|
|
Style Transfer (HP)
|
100% |
32628
41.9 IPS |
|
|
Style Transfer (Q)
|
96% |
32736
42.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5782
213.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6026
222.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5400
199.4 IPS |
|
|
Text Classification (SP)
|
100% |
3200
4.27 KIPS |
|
|
Text Classification (HP)
|
99% |
5669
7.57 KIPS |
|
|
Text Classification (Q)
|
93% |
5604
7.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
1315
22.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1379
23.8 IPS |
|
|
Machine Translation (Q)
|
98% |
1385
23.9 IPS |
