iPhone 15 Pro
Geekbench AI Score
3831
Single Precision Score
25272
Half Precision Score
35535
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | hrdc0r3 |
| Upload Date | August 20 2025 06:09 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.6.1 |
| 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% |
1611
299.5 IPS |
|
|
Image Classification (HP)
|
100% |
10744
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15959
2.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1569
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16312
264.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21411
347.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7465
8.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
104633
122.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
206253
241.7 IPS |
|
|
Object Detection (SP)
|
100% |
1747
138.5 IPS |
|
|
Object Detection (HP)
|
100% |
13763
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18793
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3105
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
33964
403.6 IPS |
|
|
Face Detection (Q)
|
100% |
53442
635.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6725
51.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
77930
600.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
127263
995.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20349
26.2 IPS |
|
|
Style Transfer (HP)
|
100% |
208429
267.9 IPS |
|
|
Style Transfer (Q)
|
96% |
247798
319.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4642
171.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34474
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56156
2.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3279
4.38 KIPS |
|
|
Text Classification (HP)
|
100% |
3338
4.46 KIPS |
|
|
Text Classification (Q)
|
93% |
3478
4.67 KIPS |
|
|
Machine Translation (SP)
|
100% |
3195
55.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6633
114.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7366
127.3 IPS |
