iPhone 15 Pro
Geekbench AI Score
3859
Single Precision Score
25206
Half Precision Score
36310
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | davidblue |
| Upload Date | June 02 2025 07:17 AM |
| Views | 9 |
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% |
1671
310.8 IPS |
|
|
Image Classification (HP)
|
100% |
10971
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
16307
3.04 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1591
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16753
271.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21666
351.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7681
8.96 IPS |
|
|
Pose Estimation (HP)
|
100% |
102996
120.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
204421
239.6 IPS |
|
|
Object Detection (SP)
|
100% |
1746
138.5 IPS |
|
|
Object Detection (HP)
|
100% |
13874
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19079
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3137
37.3 IPS |
|
|
Face Detection (HP)
|
100% |
34409
408.9 IPS |
|
|
Face Detection (Q)
|
100% |
52988
629.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6713
51.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78525
605.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
126277
987.3 IPS |
|
|
Style Transfer (SP)
|
100% |
20430
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
202361
260.1 IPS |
|
|
Style Transfer (Q)
|
96% |
255434
329.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4690
173.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33759
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
63074
2.33 KIPS |
|
|
Text Classification (SP)
|
100% |
3236
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
3263
4.36 KIPS |
|
|
Text Classification (Q)
|
93% |
3274
4.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
3148
54.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6546
112.8 IPS |
|
|
Machine Translation (Q)
|
98% |
8191
141.6 IPS |
