iPhone 15 Pro
Geekbench AI Score
3759
Single Precision Score
26766
Half Precision Score
36361
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | November 25 2025 11:22 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
1555
289.3 IPS |
|
|
Image Classification (HP)
|
100% |
11119
2.07 KIPS |
|
|
Image Classification (Q)
|
97% |
15305
2.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1528
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16602
269.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
21283
345.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7298
8.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
105258
122.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
204238
239.4 IPS |
|
|
Object Detection (SP)
|
100% |
1656
131.3 IPS |
|
|
Object Detection (HP)
|
100% |
13460
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
17469
1.40 KIPS |
|
|
Face Detection (SP)
|
100% |
3065
36.4 IPS |
|
|
Face Detection (HP)
|
100% |
36300
431.3 IPS |
|
|
Face Detection (Q)
|
100% |
51410
610.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6610
50.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78357
603.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
123518
965.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20460
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
206370
265.3 IPS |
|
|
Style Transfer (Q)
|
96% |
247529
319.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4564
168.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34638
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56242
2.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3255
4.34 KIPS |
|
|
Text Classification (HP)
|
99% |
5363
7.16 KIPS |
|
|
Text Classification (Q)
|
93% |
5737
7.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
3186
54.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6619
114.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6855
118.5 IPS |
