iPhone 13 Pro Max
Geekbench AI Score
3223
Single Precision Score
19282
Half Precision Score
21966
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 09 2024 05:28 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone 13 Pro Max |
| Model ID | iPhone14,3 |
| Motherboard | D64AP |
| 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 | 5.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1355
252.0 IPS |
|
|
Image Classification (HP)
|
100% |
8795
1.64 KIPS |
|
|
Image Classification (Q)
|
96% |
11169
2.09 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1288
20.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12139
196.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
14136
229.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6427
7.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
92041
107.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
94497
110.8 IPS |
|
|
Object Detection (SP)
|
100% |
1441
114.3 IPS |
|
|
Object Detection (HP)
|
99% |
10694
850.7 IPS |
|
|
Object Detection (Q)
|
91% |
12341
986.1 IPS |
|
|
Face Detection (SP)
|
100% |
2607
31.0 IPS |
|
|
Face Detection (HP)
|
100% |
28105
334.0 IPS |
|
|
Face Detection (Q)
|
100% |
35516
422.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5062
39.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
55843
430.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
72354
565.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17431
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
150154
193.0 IPS |
|
|
Style Transfer (Q)
|
96% |
151088
195.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3957
146.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26962
995.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
29240
1.08 KIPS |
|
|
Text Classification (SP)
|
100% |
2444
3.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2313
3.09 KIPS |
|
|
Text Classification (Q)
|
93% |
2372
3.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
3365
58.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4601
79.2 IPS |
|
|
Machine Translation (Q)
|
98% |
5276
91.2 IPS |
