iPhone 16 Pro ANE iPhone17,1
Geekbench AI Score
4639
Single Precision Score
32186
Half Precision Score
44493
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | MiKayule |
| Upload Date | October 12 2024 11:48 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0.1 |
| 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% |
2019
375.4 IPS |
|
|
Image Classification (HP)
|
100% |
15250
2.84 KIPS |
|
|
Image Classification (Q)
|
97% |
20621
3.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1988
32.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
14726
238.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
18342
297.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9340
10.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
154364
180.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
292930
343.3 IPS |
|
|
Object Detection (SP)
|
100% |
2181
173.0 IPS |
|
|
Object Detection (HP)
|
100% |
16365
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22640
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3711
44.1 IPS |
|
|
Face Detection (HP)
|
100% |
41390
491.8 IPS |
|
|
Face Detection (Q)
|
100% |
57075
678.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
8052
62.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
95506
735.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
162475
1.27 KIPS |
|
|
Style Transfer (SP)
|
100% |
24788
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
245598
315.7 IPS |
|
|
Style Transfer (Q)
|
96% |
301586
389.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5743
212.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50788
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85003
3.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3431
4.58 KIPS |
|
|
Text Classification (HP)
|
100% |
4364
5.82 KIPS |
|
|
Text Classification (Q)
|
93% |
4403
5.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
3870
66.7 IPS |
|
|
Machine Translation (HP)
|
100% |
9774
168.4 IPS |
|
|
Machine Translation (Q)
|
98% |
11581
200.1 IPS |
