iPhone17,1
Geekbench AI Score
5455
Single Precision Score
6065
Half Precision Score
5494
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | cheltenham |
| Upload Date | September 30 2024 06:27 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
2697
501.5 IPS |
|
|
Image Classification (HP)
|
100% |
2277
423.5 IPS |
|
|
Image Classification (Q)
|
97% |
2627
490.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
3551
57.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
4375
70.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4299
69.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
14158
16.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
13443
15.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
13526
15.9 IPS |
|
|
Object Detection (SP)
|
100% |
3360
266.5 IPS |
|
|
Object Detection (HP)
|
100% |
3409
270.4 IPS |
|
|
Object Detection (Q)
|
91% |
2697
215.5 IPS |
|
|
Face Detection (SP)
|
100% |
7785
92.5 IPS |
|
|
Face Detection (HP)
|
100% |
10619
126.2 IPS |
|
|
Face Detection (Q)
|
100% |
7028
83.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
13299
102.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
14266
109.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
11076
86.6 IPS |
|
|
Style Transfer (SP)
|
100% |
32547
41.8 IPS |
|
|
Style Transfer (HP)
|
100% |
32155
41.3 IPS |
|
|
Style Transfer (Q)
|
96% |
35109
45.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8071
298.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8425
311.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6797
251.0 IPS |
|
|
Text Classification (SP)
|
100% |
3453
4.61 KIPS |
|
|
Text Classification (HP)
|
100% |
5844
7.80 KIPS |
|
|
Text Classification (Q)
|
93% |
5777
7.75 KIPS |
|
|
Machine Translation (SP)
|
100% |
546
9.40 IPS |
|
|
Machine Translation (HP)
|
100% |
616
10.6 IPS |
|
|
Machine Translation (Q)
|
98% |
567
9.80 IPS |
