iPhone 15 Pro
Geekbench AI Score
4301
Single Precision Score
4934
Half Precision Score
4762
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | wp4 |
| Upload Date | September 12 2025 05:42 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| 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% |
977
181.7 IPS |
|
|
Image Classification (HP)
|
100% |
914
170.1 IPS |
|
|
Image Classification (Q)
|
96% |
830
154.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3659
59.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
4131
67.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
4065
65.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
13152
15.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
14865
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
14365
16.8 IPS |
|
|
Object Detection (SP)
|
100% |
1714
136.0 IPS |
|
|
Object Detection (HP)
|
100% |
1765
140.0 IPS |
|
|
Object Detection (Q)
|
92% |
1758
140.3 IPS |
|
|
Face Detection (SP)
|
100% |
5548
65.9 IPS |
|
|
Face Detection (HP)
|
100% |
6982
83.0 IPS |
|
|
Face Detection (Q)
|
100% |
5468
65.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
10958
84.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
11961
92.2 IPS |
|
|
Depth Estimation (Q)
|
86% |
11432
89.3 IPS |
|
|
Style Transfer (SP)
|
100% |
26943
34.6 IPS |
|
|
Style Transfer (HP)
|
100% |
31809
40.9 IPS |
|
|
Style Transfer (Q)
|
96% |
31526
40.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4529
167.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4545
167.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4363
161.1 IPS |
|
|
Text Classification (SP)
|
100% |
3219
4.30 KIPS |
|
|
Text Classification (HP)
|
99% |
5489
7.33 KIPS |
|
|
Text Classification (Q)
|
93% |
5511
7.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
1128
19.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1305
22.5 IPS |
|
|
Machine Translation (Q)
|
98% |
1488
25.7 IPS |
