iPhone 15 Pro Max
Geekbench AI Score
4029
Single Precision Score
24752
Half Precision Score
34543
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 25 2024 05:37 PM |
| 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% |
1708
317.6 IPS |
|
|
Image Classification (HP)
|
100% |
10753
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15757
2.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1608
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15534
251.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
20659
334.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8483
9.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
106142
123.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
203598
238.6 IPS |
|
|
Object Detection (SP)
|
100% |
1839
145.9 IPS |
|
|
Object Detection (HP)
|
100% |
13811
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18763
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3194
37.9 IPS |
|
|
Face Detection (HP)
|
100% |
33443
397.4 IPS |
|
|
Face Detection (Q)
|
100% |
49587
589.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7179
55.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78547
605.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
128307
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
22083
28.4 IPS |
|
|
Style Transfer (HP)
|
100% |
204890
263.4 IPS |
|
|
Style Transfer (Q)
|
96% |
246683
318.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5232
193.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33620
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58444
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3197
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3188
4.25 KIPS |
|
|
Text Classification (Q)
|
93% |
2922
3.92 KIPS |
|
|
Machine Translation (SP)
|
100% |
3113
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6111
105.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7259
125.4 IPS |
