iPhone 15 Pro
Geekbench AI Score
3843
Single Precision Score
6980
Half Precision Score
5715
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | wp4 |
| Upload Date | September 11 2025 08:38 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1567
291.4 IPS |
|
|
Image Classification (HP)
|
100% |
2951
548.7 IPS |
|
|
Image Classification (Q)
|
96% |
2037
380.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1551
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2367
38.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
3029
49.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7784
9.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
17030
19.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
14580
17.1 IPS |
|
|
Object Detection (SP)
|
100% |
1682
133.4 IPS |
|
|
Object Detection (HP)
|
97% |
3306
263.2 IPS |
|
|
Object Detection (Q)
|
94% |
2379
189.6 IPS |
|
|
Face Detection (SP)
|
100% |
3149
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
6820
81.0 IPS |
|
|
Face Detection (Q)
|
100% |
3860
45.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6926
53.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
12837
99.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
9025
70.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21370
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
34307
44.1 IPS |
|
|
Style Transfer (Q)
|
96% |
28229
36.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4682
172.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5674
209.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4382
161.8 IPS |
|
|
Text Classification (SP)
|
100% |
3227
4.31 KIPS |
|
|
Text Classification (HP)
|
99% |
5505
7.35 KIPS |
|
|
Text Classification (Q)
|
93% |
5399
7.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
3142
54.1 IPS |
|
|
Machine Translation (HP)
|
98% |
7447
128.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7469
129.1 IPS |
