iPhone17,2
Geekbench AI Score
4500
Single Precision Score
7744
Half Precision Score
6182
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | esahins |
| Upload Date | November 12 2024 02:18 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0.1 |
| Model | iPhone17,2 |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1990
370.1 IPS |
|
|
Image Classification (HP)
|
100% |
3360
624.9 IPS |
|
|
Image Classification (Q)
|
96% |
2275
424.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1953
31.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2908
47.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3374
54.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8779
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
18132
21.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15357
18.0 IPS |
|
|
Object Detection (SP)
|
100% |
2057
163.1 IPS |
|
|
Object Detection (HP)
|
97% |
3808
303.1 IPS |
|
|
Object Detection (Q)
|
94% |
2637
210.2 IPS |
|
|
Face Detection (SP)
|
100% |
3561
42.3 IPS |
|
|
Face Detection (HP)
|
100% |
7501
89.1 IPS |
|
|
Face Detection (Q)
|
100% |
4251
50.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
7764
59.8 IPS |
|
|
Depth Estimation (HP)
|
97% |
14219
109.9 IPS |
|
|
Depth Estimation (Q)
|
86% |
9890
77.2 IPS |
|
|
Style Transfer (SP)
|
100% |
24184
31.1 IPS |
|
|
Style Transfer (HP)
|
100% |
37594
48.3 IPS |
|
|
Style Transfer (Q)
|
96% |
30748
39.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5636
208.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6940
256.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4999
184.6 IPS |
|
|
Text Classification (SP)
|
100% |
3425
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
5834
7.79 KIPS |
|
|
Text Classification (Q)
|
93% |
5796
7.78 KIPS |
|
|
Machine Translation (SP)
|
100% |
3762
64.8 IPS |
|
|
Machine Translation (HP)
|
98% |
7086
122.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7003
121.0 IPS |
