iPhone 15 Pro Max
Geekbench AI Score
3857
Single Precision Score
24035
Half Precision Score
33763
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 06 2024 02:52 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% |
1630
303.1 IPS |
|
|
Image Classification (HP)
|
100% |
10830
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
14667
2.74 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1587
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
15692
254.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21097
342.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7567
8.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
104367
121.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
203053
238.0 IPS |
|
|
Object Detection (SP)
|
100% |
1762
139.8 IPS |
|
|
Object Detection (HP)
|
100% |
13530
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18884
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3102
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
33623
399.5 IPS |
|
|
Face Detection (Q)
|
100% |
50592
601.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6856
52.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
77976
600.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
127650
998.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20677
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
201452
259.0 IPS |
|
|
Style Transfer (Q)
|
96% |
245536
316.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4836
178.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33769
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57371
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3201
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
2499
3.34 KIPS |
|
|
Text Classification (Q)
|
93% |
2381
3.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3109
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6017
103.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7491
129.4 IPS |
