iPhone 15 Pro Max
Geekbench AI Score
3845
Single Precision Score
24675
Half Precision Score
34381
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 25 2024 03:28 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1650
306.8 IPS |
|
|
Image Classification (HP)
|
100% |
11150
2.07 KIPS |
|
|
Image Classification (Q)
|
97% |
15558
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1574
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
15681
254.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
20876
338.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7400
8.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
102063
119.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
201887
236.6 IPS |
|
|
Object Detection (SP)
|
100% |
1742
138.2 IPS |
|
|
Object Detection (HP)
|
100% |
13848
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19081
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3086
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
33627
399.6 IPS |
|
|
Face Detection (Q)
|
100% |
50068
594.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6932
53.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78178
602.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
128534
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
20414
26.2 IPS |
|
|
Style Transfer (HP)
|
100% |
203447
261.5 IPS |
|
|
Style Transfer (Q)
|
96% |
245256
316.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4783
176.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33725
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58002
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3260
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
3111
4.15 KIPS |
|
|
Text Classification (Q)
|
93% |
2653
3.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
3102
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6036
104.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7596
131.3 IPS |
