iPhone 15 Pro Max
Geekbench AI Score
3839
Single Precision Score
25161
Half Precision Score
34602
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 30 2024 06:23 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% |
1693
314.8 IPS |
|
|
Image Classification (HP)
|
100% |
11222
2.09 KIPS |
|
|
Image Classification (Q)
|
97% |
15180
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1624
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15680
254.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
20783
336.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8049
9.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
106559
124.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
202577
237.4 IPS |
|
|
Object Detection (SP)
|
100% |
1780
141.2 IPS |
|
|
Object Detection (HP)
|
100% |
13657
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19041
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3123
37.1 IPS |
|
|
Face Detection (HP)
|
100% |
33817
401.8 IPS |
|
|
Face Detection (Q)
|
100% |
50918
605.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6964
53.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78481
604.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
123969
969.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21089
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
181896
233.8 IPS |
|
|
Style Transfer (Q)
|
96% |
237908
307.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3956
146.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33881
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59528
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3209
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
3528
4.71 KIPS |
|
|
Text Classification (Q)
|
93% |
3340
4.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
3034
52.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6884
118.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6773
117.0 IPS |
