iPhone17,5
Geekbench AI Score
1854
Single Precision Score
14896
Half Precision Score
20722
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | cellphonehater |
| Upload Date | March 31 2025 05:35 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.3.2 |
| Model | iPhone17,5 |
| Model ID | iPhone17,5 |
| Motherboard | V59AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 1.62 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
839
156.0 IPS |
|
|
Image Classification (HP)
|
100% |
7887
1.47 KIPS |
|
|
Image Classification (Q)
|
97% |
10530
1.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
730
11.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
8248
133.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
10805
175.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
3753
4.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
62691
73.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
123330
144.6 IPS |
|
|
Object Detection (SP)
|
100% |
955
75.7 IPS |
|
|
Object Detection (HP)
|
100% |
7462
591.9 IPS |
|
|
Object Detection (Q)
|
91% |
10664
852.1 IPS |
|
|
Face Detection (SP)
|
100% |
1442
17.1 IPS |
|
|
Face Detection (HP)
|
100% |
17463
207.5 IPS |
|
|
Face Detection (Q)
|
100% |
24685
293.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
3508
27.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
41806
322.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
72802
569.2 IPS |
|
|
Style Transfer (SP)
|
100% |
10197
13.1 IPS |
|
|
Style Transfer (HP)
|
100% |
111020
142.7 IPS |
|
|
Style Transfer (Q)
|
96% |
141853
183.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2505
92.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
23867
881.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
37459
1.38 KIPS |
|
|
Text Classification (SP)
|
100% |
1395
1.86 KIPS |
|
|
Text Classification (HP)
|
100% |
1946
2.60 KIPS |
|
|
Text Classification (Q)
|
93% |
2078
2.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
1217
21.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4697
80.9 IPS |
|
|
Machine Translation (Q)
|
98% |
4917
85.0 IPS |
