iPhone 15 Pro Max
Geekbench AI Score
3842
Single Precision Score
21519
Half Precision Score
27500
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | anh |
| Upload Date | August 16 2024 02:52 PM |
| Views | 21 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1649
306.6 IPS |
|
|
Image Classification (HP)
|
100% |
11374
2.12 KIPS |
|
|
Image Classification (Q)
|
99% |
12953
2.42 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1621
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
10509
170.4 IPS |
|
|
Image Segmentation (Q)
|
100% |
10964
177.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7537
8.79 IPS |
|
|
Pose Estimation (HP)
|
100% |
101772
118.8 IPS |
|
|
Pose Estimation (Q)
|
94% |
197756
232.0 IPS |
|
|
Object Detection (SP)
|
100% |
1758
139.4 IPS |
|
|
Object Detection (HP)
|
100% |
12847
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
18533
1.48 KIPS |
|
|
Face Detection (SP)
|
100% |
3123
37.1 IPS |
|
|
Face Detection (HP)
|
100% |
21781
258.8 IPS |
|
|
Face Detection (Q)
|
100% |
36663
435.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6883
53.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
63726
491.0 IPS |
|
|
Depth Estimation (Q)
|
97% |
73921
571.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20250
26.0 IPS |
|
|
Style Transfer (HP)
|
100% |
137552
176.8 IPS |
|
|
Style Transfer (Q)
|
100% |
138740
178.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4738
175.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
36130
1.33 KIPS |
|
|
Image Super-Resolution (Q)
|
98% |
53372
1.98 KIPS |
|
|
Text Classification (SP)
|
100% |
3093
4.13 KIPS |
|
|
Text Classification (HP)
|
100% |
3280
4.38 KIPS |
|
|
Text Classification (Q)
|
93% |
3120
4.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
3109
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6024
103.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7592
131.2 IPS |
