iPhone 15 Pro
Geekbench AI Score
3876
Single Precision Score
27345
Half Precision Score
37150
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Luclucdave |
| Upload Date | June 22 2025 10:36 AM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 19.0 |
| 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% |
1657
308.1 IPS |
|
|
Image Classification (HP)
|
100% |
11004
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15115
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1620
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
16502
267.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21188
343.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7798
9.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
105212
122.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
205955
241.4 IPS |
|
|
Object Detection (SP)
|
100% |
1756
139.3 IPS |
|
|
Object Detection (HP)
|
100% |
13785
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
17404
1.39 KIPS |
|
|
Face Detection (SP)
|
100% |
3143
37.3 IPS |
|
|
Face Detection (HP)
|
100% |
36291
431.2 IPS |
|
|
Face Detection (Q)
|
100% |
49448
587.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6856
52.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78160
602.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
125311
979.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20969
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
207946
267.3 IPS |
|
|
Style Transfer (Q)
|
96% |
252553
325.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4787
176.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35034
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57140
2.11 KIPS |
|
|
Text Classification (SP)
|
100% |
2988
3.99 KIPS |
|
|
Text Classification (HP)
|
100% |
5240
6.99 KIPS |
|
|
Text Classification (Q)
|
93% |
5288
7.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
3226
55.6 IPS |
|
|
Machine Translation (HP)
|
100% |
8198
141.2 IPS |
|
|
Machine Translation (Q)
|
98% |
9225
159.4 IPS |
