iPhone 13 Pro Max
Geekbench AI Score
3283
Single Precision Score
19890
Half Precision Score
23528
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 13 2025 11:30 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1342
249.6 IPS |
|
|
Image Classification (HP)
|
100% |
7911
1.47 KIPS |
|
|
Image Classification (Q)
|
96% |
11295
2.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1276
20.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12083
195.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
15084
244.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6584
7.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
90771
105.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
96622
113.2 IPS |
|
|
Object Detection (SP)
|
100% |
1454
115.3 IPS |
|
|
Object Detection (HP)
|
99% |
11075
881.0 IPS |
|
|
Object Detection (Q)
|
91% |
11872
948.6 IPS |
|
|
Face Detection (SP)
|
100% |
2682
31.9 IPS |
|
|
Face Detection (HP)
|
100% |
29022
344.8 IPS |
|
|
Face Detection (Q)
|
100% |
37037
440.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5332
41.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
58317
449.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
77206
603.3 IPS |
|
|
Style Transfer (SP)
|
100% |
17834
22.9 IPS |
|
|
Style Transfer (HP)
|
100% |
151357
194.6 IPS |
|
|
Style Transfer (Q)
|
96% |
170115
219.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3913
144.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25666
947.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
30236
1.12 KIPS |
|
|
Text Classification (SP)
|
100% |
2442
3.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2461
3.29 KIPS |
|
|
Text Classification (Q)
|
93% |
2480
3.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
3644
62.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6235
107.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7292
126.0 IPS |
