iPhone17,1
Geekbench AI Score
5808
Single Precision Score
6774
Half Precision Score
6113
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | MarkJWilcox |
| Upload Date | November 12 2024 05:02 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
2930
545.0 IPS |
|
|
Image Classification (HP)
|
100% |
2732
508.1 IPS |
|
|
Image Classification (Q)
|
97% |
2886
538.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
3574
57.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
4460
72.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
4439
72.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
15799
18.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
16475
19.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15654
18.3 IPS |
|
|
Object Detection (SP)
|
100% |
3374
267.6 IPS |
|
|
Object Detection (HP)
|
100% |
3572
283.3 IPS |
|
|
Object Detection (Q)
|
91% |
3188
254.7 IPS |
|
|
Face Detection (SP)
|
100% |
7715
91.7 IPS |
|
|
Face Detection (HP)
|
100% |
10906
129.6 IPS |
|
|
Face Detection (Q)
|
100% |
7293
86.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
13267
102.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
14575
112.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
12241
95.7 IPS |
|
|
Style Transfer (SP)
|
100% |
33131
42.6 IPS |
|
|
Style Transfer (HP)
|
100% |
38025
48.9 IPS |
|
|
Style Transfer (Q)
|
96% |
36577
47.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8136
300.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8518
314.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7000
258.5 IPS |
|
|
Text Classification (SP)
|
100% |
3432
4.58 KIPS |
|
|
Text Classification (HP)
|
100% |
5904
7.88 KIPS |
|
|
Text Classification (Q)
|
93% |
5896
7.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
827
14.3 IPS |
|
|
Machine Translation (HP)
|
100% |
934
16.1 IPS |
|
|
Machine Translation (Q)
|
98% |
846
14.6 IPS |
