iPhone 13 Pro
Geekbench AI Score
3144
Single Precision Score
16531
Half Precision Score
18539
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | JoshuaChung |
| Upload Date | September 20 2024 04:42 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 13 Pro |
| Model ID | iPhone14,2 |
| Motherboard | D63AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1266
235.4 IPS |
|
|
Image Classification (HP)
|
100% |
7543
1.40 KIPS |
|
|
Image Classification (Q)
|
96% |
9721
1.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1307
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
6941
112.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
7734
125.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5768
6.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
88284
103.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
93720
109.8 IPS |
|
|
Object Detection (SP)
|
100% |
1388
110.1 IPS |
|
|
Object Detection (HP)
|
99% |
10419
828.8 IPS |
|
|
Object Detection (Q)
|
91% |
12497
998.5 IPS |
|
|
Face Detection (SP)
|
100% |
2575
30.6 IPS |
|
|
Face Detection (HP)
|
100% |
27459
326.3 IPS |
|
|
Face Detection (Q)
|
100% |
33379
396.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5333
41.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
54314
418.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
71715
560.4 IPS |
|
|
Style Transfer (SP)
|
100% |
16339
21.0 IPS |
|
|
Style Transfer (HP)
|
100% |
154279
198.3 IPS |
|
|
Style Transfer (Q)
|
96% |
154276
199.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3875
143.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26577
981.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
28688
1.06 KIPS |
|
|
Text Classification (SP)
|
100% |
2412
3.22 KIPS |
|
|
Text Classification (HP)
|
100% |
2317
3.09 KIPS |
|
|
Text Classification (Q)
|
93% |
2376
3.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
3402
58.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2234
38.5 IPS |
|
|
Machine Translation (Q)
|
98% |
2164
37.4 IPS |
