iPhone 15 Pro Max
Geekbench AI Score
3772
Single Precision Score
24595
Half Precision Score
34309
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 21 2024 03:13 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% |
1623
301.8 IPS |
|
|
Image Classification (HP)
|
100% |
11218
2.09 KIPS |
|
|
Image Classification (Q)
|
97% |
15702
2.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
15432
250.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
20508
332.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7453
8.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
103307
120.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
201149
235.8 IPS |
|
|
Object Detection (SP)
|
100% |
1724
136.7 IPS |
|
|
Object Detection (HP)
|
100% |
13587
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18770
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
2924
34.7 IPS |
|
|
Face Detection (HP)
|
100% |
33547
398.6 IPS |
|
|
Face Detection (Q)
|
100% |
49712
590.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6643
51.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
79497
612.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
126526
989.2 IPS |
|
|
Style Transfer (SP)
|
100% |
19956
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
202016
259.7 IPS |
|
|
Style Transfer (Q)
|
96% |
246965
318.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4676
172.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33662
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57536
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3170
4.23 KIPS |
|
|
Text Classification (HP)
|
100% |
3090
4.12 KIPS |
|
|
Text Classification (Q)
|
93% |
3163
4.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
3060
52.7 IPS |
|
|
Machine Translation (HP)
|
100% |
5949
102.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6577
113.7 IPS |
