iPhone 15 Pro
Geekbench AI Score
3974
Single Precision Score
27940
Half Precision Score
39534
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | March 18 2026 05:05 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.4 |
| 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% |
1617
300.8 IPS |
|
|
Image Classification (HP)
|
100% |
10622
1.98 KIPS |
|
|
Image Classification (Q)
|
97% |
15075
2.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1570
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16417
266.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
22015
356.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7025
8.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
105562
123.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
208174
244.0 IPS |
|
|
Object Detection (SP)
|
100% |
1683
133.5 IPS |
|
|
Object Detection (HP)
|
100% |
13908
1.10 KIPS |
|
|
Object Detection (Q)
|
89% |
18520
1.48 KIPS |
|
|
Face Detection (SP)
|
100% |
3172
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
36345
431.9 IPS |
|
|
Face Detection (Q)
|
100% |
57610
684.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6660
51.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78361
603.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
127343
995.1 IPS |
|
|
Style Transfer (SP)
|
100% |
19698
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
207910
267.3 IPS |
|
|
Style Transfer (Q)
|
96% |
251004
323.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4427
163.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34834
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57978
2.14 KIPS |
|
|
Text Classification (SP)
|
99% |
5659
7.55 KIPS |
|
|
Text Classification (HP)
|
99% |
8488
11.3 KIPS |
|
|
Text Classification (Q)
|
92% |
9343
12.6 KIPS |
|
|
Machine Translation (SP)
|
100% |
3142
54.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6470
111.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7308
126.3 IPS |
