iPhone 15 Pro
Geekbench AI Score
3582
Single Precision Score
22708
Half Precision Score
32809
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | jw154j |
| Upload Date | September 11 2025 01:59 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1513
281.4 IPS |
|
|
Image Classification (HP)
|
100% |
9065
1.69 KIPS |
|
|
Image Classification (Q)
|
97% |
11819
2.21 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1484
24.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16437
266.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21090
341.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6719
7.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
98020
114.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
187056
219.2 IPS |
|
|
Object Detection (SP)
|
100% |
1595
126.5 IPS |
|
|
Object Detection (HP)
|
100% |
10788
855.7 IPS |
|
|
Object Detection (Q)
|
91% |
16251
1.30 KIPS |
|
|
Face Detection (SP)
|
100% |
2897
34.4 IPS |
|
|
Face Detection (HP)
|
100% |
34173
406.1 IPS |
|
|
Face Detection (Q)
|
100% |
50388
598.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6300
48.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
59532
458.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
91099
712.2 IPS |
|
|
Style Transfer (SP)
|
100% |
19202
24.7 IPS |
|
|
Style Transfer (HP)
|
100% |
189728
243.9 IPS |
|
|
Style Transfer (Q)
|
96% |
227423
293.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4207
155.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25806
952.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
50789
1.88 KIPS |
|
|
Text Classification (SP)
|
100% |
3235
4.32 KIPS |
|
|
Text Classification (HP)
|
99% |
5601
7.48 KIPS |
|
|
Text Classification (Q)
|
93% |
5551
7.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
3037
52.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4149
71.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6481
112.0 IPS |
