iPhone 15 Pro
Geekbench AI Score
3950
Single Precision Score
25386
Half Precision Score
34716
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | iClondike |
| Upload Date | August 02 2025 07:42 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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% |
1707
317.4 IPS |
|
|
Image Classification (HP)
|
100% |
10969
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
15447
2.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1574
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
16464
266.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21082
341.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
8096
9.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
106123
123.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
207040
242.7 IPS |
|
|
Object Detection (SP)
|
100% |
1769
140.3 IPS |
|
|
Object Detection (HP)
|
100% |
14003
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
19083
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3147
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
36821
437.5 IPS |
|
|
Face Detection (Q)
|
100% |
53858
640.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6963
53.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78484
604.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
128056
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21370
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
203878
262.1 IPS |
|
|
Style Transfer (Q)
|
96% |
252024
325.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4884
180.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34211
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55456
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3285
4.38 KIPS |
|
|
Text Classification (HP)
|
100% |
3123
4.17 KIPS |
|
|
Text Classification (Q)
|
93% |
2628
3.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
3206
55.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6581
113.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7802
134.8 IPS |
