iPhone 15 Pro
Geekbench AI Score
2719
Single Precision Score
14605
Half Precision Score
18053
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | jdabney |
| Upload Date | September 10 2024 01:47 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1460
271.5 IPS |
|
|
Image Classification (HP)
|
100% |
6206
1.15 KIPS |
|
|
Image Classification (Q)
|
97% |
7777
1.45 KIPS |
|
|
Image Segmentation (SP)
|
100% |
807
13.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5193
84.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
9855
159.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7347
8.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
88048
102.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
152939
179.3 IPS |
|
|
Object Detection (SP)
|
100% |
1491
118.2 IPS |
|
|
Object Detection (HP)
|
100% |
8530
676.6 IPS |
|
|
Object Detection (Q)
|
93% |
10028
800.1 IPS |
|
|
Face Detection (SP)
|
100% |
2187
26.0 IPS |
|
|
Face Detection (HP)
|
100% |
11217
133.3 IPS |
|
|
Face Detection (Q)
|
100% |
13317
158.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4677
36.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
42729
329.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
57919
452.8 IPS |
|
|
Style Transfer (SP)
|
100% |
12221
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
128336
165.0 IPS |
|
|
Style Transfer (Q)
|
96% |
138116
178.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4125
152.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18495
682.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
26880
992.5 IPS |
|
|
Text Classification (SP)
|
100% |
1762
2.35 KIPS |
|
|
Text Classification (HP)
|
71% |
6205
8.92 KIPS |
|
|
Text Classification (Q)
|
69% |
4362
6.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1888
32.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2586
44.5 IPS |
|
|
Machine Translation (Q)
|
98% |
2505
43.3 IPS |
