iPhone 13 Pro Max
Geekbench AI Score
2206
Single Precision Score
10315
Half Precision Score
11703
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | ElementalOwl |
| Upload Date | September 14 2024 07:10 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 5.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1195
222.2 IPS |
|
|
Image Classification (HP)
|
100% |
3703
688.6 IPS |
|
|
Image Classification (Q)
|
96% |
5068
946.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
669
10.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3839
62.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
6082
98.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5886
6.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
74544
87.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
76330
89.5 IPS |
|
|
Object Detection (SP)
|
100% |
1238
98.2 IPS |
|
|
Object Detection (HP)
|
99% |
5611
446.3 IPS |
|
|
Object Detection (Q)
|
93% |
6158
491.3 IPS |
|
|
Face Detection (SP)
|
100% |
1914
22.7 IPS |
|
|
Face Detection (HP)
|
100% |
10523
125.0 IPS |
|
|
Face Detection (Q)
|
100% |
12341
146.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
3834
29.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
35231
271.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
43527
340.1 IPS |
|
|
Style Transfer (SP)
|
100% |
10385
13.4 IPS |
|
|
Style Transfer (HP)
|
100% |
96083
123.5 IPS |
|
|
Style Transfer (Q)
|
95% |
79829
103.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3110
114.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
12932
477.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15035
555.2 IPS |
|
|
Text Classification (SP)
|
100% |
1290
1.72 KIPS |
|
|
Text Classification (HP)
|
100% |
2257
3.01 KIPS |
|
|
Text Classification (Q)
|
93% |
2286
3.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
1538
26.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2206
38.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2258
39.0 IPS |
