iPhone 13 Pro Max
Geekbench AI Score
3278
Single Precision Score
20057
Half Precision Score
23097
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | Ryan900 |
| Upload Date | July 29 2025 07:27 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.6 |
| 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% |
1352
251.5 IPS |
|
|
Image Classification (HP)
|
100% |
8188
1.52 KIPS |
|
|
Image Classification (Q)
|
96% |
9737
1.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1267
20.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
13327
216.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
15399
249.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6433
7.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
93566
109.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
96364
112.9 IPS |
|
|
Object Detection (SP)
|
100% |
1439
114.2 IPS |
|
|
Object Detection (HP)
|
99% |
10342
822.7 IPS |
|
|
Object Detection (Q)
|
91% |
11958
955.5 IPS |
|
|
Face Detection (SP)
|
100% |
2697
32.0 IPS |
|
|
Face Detection (HP)
|
100% |
29235
347.4 IPS |
|
|
Face Detection (Q)
|
100% |
36961
439.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5374
41.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
55455
427.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
75527
590.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17699
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
150761
193.8 IPS |
|
|
Style Transfer (Q)
|
96% |
170839
220.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3894
143.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26626
983.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
29112
1.07 KIPS |
|
|
Text Classification (SP)
|
100% |
2468
3.29 KIPS |
|
|
Text Classification (HP)
|
100% |
2499
3.34 KIPS |
|
|
Text Classification (Q)
|
93% |
2499
3.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
3674
63.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6137
105.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7210
124.6 IPS |
