iPhone17,3
Geekbench AI Score
4138
Single Precision Score
7225
Half Precision Score
5748
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | KeviNW000 |
| Upload Date | November 10 2024 08:37 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone17,3 |
| Model ID | iPhone17,3 |
| Motherboard | D47AP |
| 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 | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1931
359.1 IPS |
|
|
Image Classification (HP)
|
100% |
3147
585.3 IPS |
|
|
Image Classification (Q)
|
96% |
2175
406.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1764
28.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2841
46.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3196
51.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
8160
9.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
16717
19.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
14355
16.8 IPS |
|
|
Object Detection (SP)
|
100% |
2042
162.0 IPS |
|
|
Object Detection (HP)
|
97% |
3670
292.2 IPS |
|
|
Object Detection (Q)
|
94% |
2486
198.2 IPS |
|
|
Face Detection (SP)
|
100% |
2723
32.4 IPS |
|
|
Face Detection (HP)
|
100% |
6674
79.3 IPS |
|
|
Face Detection (Q)
|
100% |
3784
45.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7110
54.8 IPS |
|
|
Depth Estimation (HP)
|
97% |
13467
104.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
9255
72.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21932
28.2 IPS |
|
|
Style Transfer (HP)
|
100% |
35328
45.4 IPS |
|
|
Style Transfer (Q)
|
96% |
28788
37.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5030
185.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6478
239.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4673
172.5 IPS |
|
|
Text Classification (SP)
|
100% |
3453
4.61 KIPS |
|
|
Text Classification (HP)
|
100% |
5952
7.94 KIPS |
|
|
Text Classification (Q)
|
93% |
5933
7.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
3525
60.7 IPS |
|
|
Machine Translation (HP)
|
98% |
5778
99.8 IPS |
|
|
Machine Translation (Q)
|
98% |
5687
98.3 IPS |
