iPhone 15 Pro Max
Geekbench AI Score
3996
Single Precision Score
24382
Half Precision Score
33602
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 11 2024 06:40 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1705
317.1 IPS |
|
|
Image Classification (HP)
|
100% |
11329
2.11 KIPS |
|
|
Image Classification (Q)
|
97% |
15087
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1597
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12790
207.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
15702
254.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8303
9.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
106339
124.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
205901
241.3 IPS |
|
|
Object Detection (SP)
|
100% |
1805
143.2 IPS |
|
|
Object Detection (HP)
|
100% |
13516
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18751
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3220
38.3 IPS |
|
|
Face Detection (HP)
|
100% |
34001
404.0 IPS |
|
|
Face Detection (Q)
|
100% |
49300
585.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7236
55.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78971
608.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
128045
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21456
27.6 IPS |
|
|
Style Transfer (HP)
|
100% |
201621
259.2 IPS |
|
|
Style Transfer (Q)
|
96% |
250410
323.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5041
186.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34308
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54921
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3250
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
3102
4.14 KIPS |
|
|
Text Classification (Q)
|
93% |
3093
4.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
3112
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6189
106.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7472
129.1 IPS |
