iPhone 15 Pro
Geekbench AI Score
4050
Single Precision Score
23984
Half Precision Score
33399
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | iPhonedo |
| Upload Date | March 03 2025 04:32 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1719
319.6 IPS |
|
|
Image Classification (HP)
|
100% |
10526
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
15410
2.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1636
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
15708
254.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
20940
339.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8425
9.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
107074
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
205497
240.9 IPS |
|
|
Object Detection (SP)
|
100% |
1831
145.3 IPS |
|
|
Object Detection (HP)
|
100% |
13620
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18789
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3252
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
34365
408.3 IPS |
|
|
Face Detection (Q)
|
100% |
50398
598.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7157
55.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
79579
613.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
131185
1.03 KIPS |
|
|
Style Transfer (SP)
|
100% |
21610
27.8 IPS |
|
|
Style Transfer (HP)
|
100% |
204312
262.6 IPS |
|
|
Style Transfer (Q)
|
96% |
254081
327.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5092
188.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
36169
1.34 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59554
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3269
4.36 KIPS |
|
|
Text Classification (HP)
|
100% |
1922
2.57 KIPS |
|
|
Text Classification (Q)
|
93% |
1776
2.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
3272
56.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6725
115.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7804
134.9 IPS |
