iPhone 15 Pro
Geekbench AI Score
3678
Single Precision Score
26145
Half Precision Score
36164
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | eithel |
| Upload Date | January 31 2026 05:18 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2.1 |
| 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% |
1462
271.9 IPS |
|
|
Image Classification (HP)
|
100% |
10871
2.02 KIPS |
|
|
Image Classification (Q)
|
97% |
16626
3.10 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1497
24.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
16476
267.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
21143
342.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7249
8.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
103366
120.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
201302
235.9 IPS |
|
|
Object Detection (SP)
|
100% |
1632
129.5 IPS |
|
|
Object Detection (HP)
|
100% |
13430
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
16159
1.29 KIPS |
|
|
Face Detection (SP)
|
100% |
3052
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
35733
424.6 IPS |
|
|
Face Detection (Q)
|
100% |
51678
614.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6591
50.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
71667
552.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
109959
859.7 IPS |
|
|
Style Transfer (SP)
|
100% |
19713
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
200620
257.9 IPS |
|
|
Style Transfer (Q)
|
96% |
249780
322.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4419
163.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31430
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55682
2.06 KIPS |
|
|
Text Classification (SP)
|
100% |
3195
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5685
7.59 KIPS |
|
|
Text Classification (Q)
|
93% |
5807
7.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
3131
53.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6540
112.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7293
126.0 IPS |
