iPhone 15 Pro
Geekbench AI Score
5057
Single Precision Score
5970
Half Precision Score
5735
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | natkat |
| Upload Date | February 05 2026 10:05 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2.1 |
| 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% |
2053
381.8 IPS |
|
|
Image Classification (HP)
|
100% |
2117
393.7 IPS |
|
|
Image Classification (Q)
|
96% |
2081
388.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
3775
61.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
4157
67.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
4089
66.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
13099
15.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
14858
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
14509
17.0 IPS |
|
|
Object Detection (SP)
|
100% |
2309
183.2 IPS |
|
|
Object Detection (HP)
|
100% |
2585
205.0 IPS |
|
|
Object Detection (Q)
|
92% |
2470
197.2 IPS |
|
|
Face Detection (SP)
|
100% |
6501
77.2 IPS |
|
|
Face Detection (HP)
|
100% |
8689
103.2 IPS |
|
|
Face Detection (Q)
|
100% |
6820
81.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
10893
83.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
12336
95.0 IPS |
|
|
Depth Estimation (Q)
|
86% |
11165
87.2 IPS |
|
|
Style Transfer (SP)
|
100% |
26913
34.6 IPS |
|
|
Style Transfer (HP)
|
100% |
32412
41.7 IPS |
|
|
Style Transfer (Q)
|
96% |
33176
42.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5785
213.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6005
221.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5428
200.4 IPS |
|
|
Text Classification (SP)
|
100% |
3183
4.25 KIPS |
|
|
Text Classification (HP)
|
99% |
5599
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5504
7.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1330
22.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1457
25.1 IPS |
|
|
Machine Translation (Q)
|
98% |
1675
28.9 IPS |
