iPhone 15 Pro Max
Geekbench AI Score
3718
Single Precision Score
25077
Half Precision Score
34540
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 18 2024 10:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1614
300.2 IPS |
|
|
Image Classification (HP)
|
100% |
11682
2.17 KIPS |
|
|
Image Classification (Q)
|
97% |
15366
2.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1578
25.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
15629
253.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
20387
330.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6656
7.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
103046
120.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
199711
234.1 IPS |
|
|
Object Detection (SP)
|
100% |
1710
135.6 IPS |
|
|
Object Detection (HP)
|
100% |
13738
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19100
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3091
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
34454
409.4 IPS |
|
|
Face Detection (Q)
|
100% |
51166
608.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6591
50.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78345
603.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
125807
983.6 IPS |
|
|
Style Transfer (SP)
|
100% |
19294
24.8 IPS |
|
|
Style Transfer (HP)
|
100% |
201430
258.9 IPS |
|
|
Style Transfer (Q)
|
96% |
246946
318.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4546
167.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34106
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56845
2.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3174
4.24 KIPS |
|
|
Text Classification (HP)
|
100% |
3045
4.06 KIPS |
|
|
Text Classification (Q)
|
93% |
3113
4.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
3071
52.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6740
116.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7191
124.3 IPS |
