iPhone 15 Pro Max
Geekbench AI Score
3996
Single Precision Score
24749
Half Precision Score
34733
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 26 2024 02:15 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1702
316.5 IPS |
|
|
Image Classification (HP)
|
100% |
10827
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15183
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1601
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15530
251.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
20633
334.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8340
9.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
106598
124.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
204505
239.7 IPS |
|
|
Object Detection (SP)
|
100% |
1840
145.9 IPS |
|
|
Object Detection (HP)
|
100% |
13531
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18549
1.48 KIPS |
|
|
Face Detection (SP)
|
100% |
3153
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
34816
413.7 IPS |
|
|
Face Detection (Q)
|
100% |
50830
604.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7174
55.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78283
603.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
128036
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21799
28.0 IPS |
|
|
Style Transfer (HP)
|
100% |
202885
260.8 IPS |
|
|
Style Transfer (Q)
|
96% |
246219
317.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5063
186.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34593
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57747
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3050
4.07 KIPS |
|
|
Text Classification (Q)
|
93% |
3093
4.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
3103
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6095
105.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7514
129.8 IPS |
