iPhone17,1
Geekbench AI Score
5863
Single Precision Score
6864
Half Precision Score
6048
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | VampirSilphy |
| Upload Date | November 22 2024 07:27 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone17,1 |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| 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 | 7.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3058
568.8 IPS |
|
|
Image Classification (HP)
|
100% |
2898
538.9 IPS |
|
|
Image Classification (Q)
|
97% |
2948
550.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
3612
58.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
4424
71.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
4414
71.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
15834
18.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
16563
19.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
15656
18.4 IPS |
|
|
Object Detection (SP)
|
100% |
3217
255.2 IPS |
|
|
Object Detection (HP)
|
100% |
3533
280.3 IPS |
|
|
Object Detection (Q)
|
91% |
2884
230.4 IPS |
|
|
Face Detection (SP)
|
100% |
7880
93.6 IPS |
|
|
Face Detection (HP)
|
100% |
10854
129.0 IPS |
|
|
Face Detection (Q)
|
100% |
7238
86.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
13775
106.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
14481
111.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
12520
97.9 IPS |
|
|
Style Transfer (SP)
|
100% |
33125
42.6 IPS |
|
|
Style Transfer (HP)
|
100% |
39490
50.8 IPS |
|
|
Style Transfer (Q)
|
96% |
36508
47.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8167
301.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8492
313.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6828
252.1 IPS |
|
|
Text Classification (SP)
|
100% |
3430
4.58 KIPS |
|
|
Text Classification (HP)
|
100% |
5867
7.83 KIPS |
|
|
Text Classification (Q)
|
93% |
5825
7.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
848
14.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1001
17.2 IPS |
|
|
Machine Translation (Q)
|
98% |
848
14.7 IPS |
