iPhone 15
Geekbench AI Score
3485
Single Precision Score
22798
Half Precision Score
26483
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 01 2024 05:50 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 15 |
| Model ID | iPhone15,4 |
| Motherboard | D37AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.56 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1432
266.4 IPS |
|
|
Image Classification (HP)
|
100% |
9772
1.82 KIPS |
|
|
Image Classification (Q)
|
97% |
12220
2.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1466
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
14223
230.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
18235
295.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6475
7.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
94457
110.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
102511
120.1 IPS |
|
|
Object Detection (SP)
|
100% |
1587
125.9 IPS |
|
|
Object Detection (HP)
|
100% |
12720
1.01 KIPS |
|
|
Object Detection (Q)
|
91% |
14881
1.19 KIPS |
|
|
Face Detection (SP)
|
100% |
3282
39.0 IPS |
|
|
Face Detection (HP)
|
100% |
31315
372.1 IPS |
|
|
Face Detection (Q)
|
100% |
40818
485.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5921
45.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
75397
580.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
94096
735.7 IPS |
|
|
Style Transfer (SP)
|
100% |
17828
22.9 IPS |
|
|
Style Transfer (HP)
|
100% |
175580
225.7 IPS |
|
|
Style Transfer (Q)
|
96% |
172023
222.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4011
148.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31538
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36782
1.36 KIPS |
|
|
Text Classification (SP)
|
100% |
2593
3.46 KIPS |
|
|
Text Classification (HP)
|
100% |
2403
3.21 KIPS |
|
|
Text Classification (Q)
|
93% |
2549
3.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
3403
58.6 IPS |
|
|
Machine Translation (HP)
|
100% |
7231
124.6 IPS |
|
|
Machine Translation (Q)
|
98% |
8060
139.3 IPS |
