iPhone 15
Geekbench AI Score
3389
Single Precision Score
23632
Half Precision Score
27264
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | MidniteMarv |
| Upload Date | May 21 2025 01:25 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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% |
1448
269.2 IPS |
|
|
Image Classification (HP)
|
100% |
10604
1.97 KIPS |
|
|
Image Classification (Q)
|
97% |
13165
2.46 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1436
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
14330
232.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
19306
313.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6011
7.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
100362
117.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
104657
122.7 IPS |
|
|
Object Detection (SP)
|
100% |
1545
122.6 IPS |
|
|
Object Detection (HP)
|
100% |
12810
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14524
1.16 KIPS |
|
|
Face Detection (SP)
|
100% |
3113
37.0 IPS |
|
|
Face Detection (HP)
|
100% |
31626
375.8 IPS |
|
|
Face Detection (Q)
|
100% |
40077
476.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5651
43.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
75257
579.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
94926
742.2 IPS |
|
|
Style Transfer (SP)
|
100% |
16370
21.0 IPS |
|
|
Style Transfer (HP)
|
100% |
177664
228.4 IPS |
|
|
Style Transfer (Q)
|
96% |
180960
233.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3773
139.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31015
1.15 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37114
1.37 KIPS |
|
|
Text Classification (SP)
|
100% |
2684
3.58 KIPS |
|
|
Text Classification (HP)
|
100% |
2783
3.71 KIPS |
|
|
Text Classification (Q)
|
93% |
2680
3.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
3553
61.2 IPS |
|
|
Machine Translation (HP)
|
100% |
7622
131.3 IPS |
|
|
Machine Translation (Q)
|
98% |
8579
148.3 IPS |
