iPhone17,2
Geekbench AI Score
4435
Single Precision Score
32701
Half Precision Score
45314
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | gundar |
| Upload Date | September 22 2024 06:48 PM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1981
368.3 IPS |
|
|
Image Classification (HP)
|
100% |
15732
2.93 KIPS |
|
|
Image Classification (Q)
|
97% |
22599
4.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1931
31.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
14635
237.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
18178
294.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8629
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
148517
173.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
292004
342.2 IPS |
|
|
Object Detection (SP)
|
100% |
2081
165.1 IPS |
|
|
Object Detection (HP)
|
100% |
16541
1.31 KIPS |
|
|
Object Detection (Q)
|
91% |
23086
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
3468
41.2 IPS |
|
|
Face Detection (HP)
|
100% |
41201
489.6 IPS |
|
|
Face Detection (Q)
|
100% |
55084
654.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
7602
58.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
95664
737.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
161781
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
23250
29.9 IPS |
|
|
Style Transfer (HP)
|
100% |
246233
316.5 IPS |
|
|
Style Transfer (Q)
|
96% |
303040
391.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5530
204.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52689
1.95 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
87109
3.22 KIPS |
|
|
Text Classification (SP)
|
100% |
3443
4.60 KIPS |
|
|
Text Classification (HP)
|
100% |
4870
6.50 KIPS |
|
|
Text Classification (Q)
|
93% |
4864
6.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
3680
63.4 IPS |
|
|
Machine Translation (HP)
|
100% |
9930
171.0 IPS |
|
|
Machine Translation (Q)
|
98% |
11521
199.1 IPS |
