iPhone17,2
Geekbench AI Score
5713
Single Precision Score
6697
Half Precision Score
5922
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | amadeus_ha |
| Upload Date | November 08 2024 11:39 PM |
| Views | 19 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
3024
562.3 IPS |
|
|
Image Classification (HP)
|
100% |
2688
499.9 IPS |
|
|
Image Classification (Q)
|
97% |
2759
514.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3276
53.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
4392
71.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
4365
70.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
15597
18.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
16429
19.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15467
18.1 IPS |
|
|
Object Detection (SP)
|
100% |
3235
256.6 IPS |
|
|
Object Detection (HP)
|
100% |
3456
274.1 IPS |
|
|
Object Detection (Q)
|
91% |
2830
226.2 IPS |
|
|
Face Detection (SP)
|
100% |
7548
89.7 IPS |
|
|
Face Detection (HP)
|
100% |
10499
124.7 IPS |
|
|
Face Detection (Q)
|
100% |
7052
83.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
13117
101.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
14802
114.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
12011
93.9 IPS |
|
|
Style Transfer (SP)
|
100% |
32559
41.9 IPS |
|
|
Style Transfer (HP)
|
100% |
39264
50.5 IPS |
|
|
Style Transfer (Q)
|
96% |
36597
47.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7923
292.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8440
311.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6808
251.4 IPS |
|
|
Text Classification (SP)
|
100% |
3423
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
5834
7.79 KIPS |
|
|
Text Classification (Q)
|
93% |
5933
7.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
849
14.6 IPS |
|
|
Machine Translation (HP)
|
100% |
902
15.5 IPS |
|
|
Machine Translation (Q)
|
98% |
804
13.9 IPS |
