iPhone 15 Pro
Geekbench AI Score
3757
Single Precision Score
23576
Half Precision Score
33176
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | cloudit0 |
| Upload Date | January 31 2025 02:16 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1611
299.5 IPS |
|
|
Image Classification (HP)
|
100% |
11898
2.21 KIPS |
|
|
Image Classification (Q)
|
97% |
16663
3.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1563
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15538
251.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20644
334.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7292
8.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
102693
119.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
202465
237.3 IPS |
|
|
Object Detection (SP)
|
100% |
1671
132.5 IPS |
|
|
Object Detection (HP)
|
100% |
13859
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18872
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3040
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
34004
404.0 IPS |
|
|
Face Detection (Q)
|
100% |
50648
601.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6709
51.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
77647
598.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
125794
983.5 IPS |
|
|
Style Transfer (SP)
|
100% |
19746
25.4 IPS |
|
|
Style Transfer (HP)
|
100% |
203203
261.2 IPS |
|
|
Style Transfer (Q)
|
96% |
250605
323.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4550
168.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33855
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59964
2.21 KIPS |
|
|
Text Classification (SP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
1801
2.40 KIPS |
|
|
Text Classification (Q)
|
93% |
1707
2.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3110
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6165
106.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7520
130.0 IPS |
