iPhone 15
Geekbench AI Score
3496
Single Precision Score
6014
Half Precision Score
4832
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 06 2025 09:00 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| 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% |
1458
271.1 IPS |
|
|
Image Classification (HP)
|
100% |
2569
477.8 IPS |
|
|
Image Classification (Q)
|
96% |
1737
324.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1522
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2164
35.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2688
43.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6469
7.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
14233
16.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
11922
14.0 IPS |
|
|
Object Detection (SP)
|
100% |
1528
121.2 IPS |
|
|
Object Detection (HP)
|
97% |
2891
230.2 IPS |
|
|
Object Detection (Q)
|
94% |
2038
162.4 IPS |
|
|
Face Detection (SP)
|
100% |
3275
38.9 IPS |
|
|
Face Detection (HP)
|
100% |
6098
72.5 IPS |
|
|
Face Detection (Q)
|
100% |
3416
40.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5989
46.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
12017
92.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
7970
62.3 IPS |
|
|
Style Transfer (SP)
|
100% |
17884
23.0 IPS |
|
|
Style Transfer (HP)
|
100% |
27385
35.2 IPS |
|
|
Style Transfer (Q)
|
96% |
22875
29.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3954
146.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4924
181.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3667
135.4 IPS |
|
|
Text Classification (SP)
|
100% |
2648
3.53 KIPS |
|
|
Text Classification (HP)
|
100% |
4675
6.24 KIPS |
|
|
Text Classification (Q)
|
93% |
4593
6.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
3393
58.5 IPS |
|
|
Machine Translation (HP)
|
98% |
5861
101.3 IPS |
|
|
Machine Translation (Q)
|
98% |
5832
100.8 IPS |
