iPhone 15 Pro Max
Geekbench AI Score
3898
Single Precision Score
23751
Half Precision Score
33190
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 18 2024 02:35 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% |
1695
315.3 IPS |
|
|
Image Classification (HP)
|
100% |
11303
2.10 KIPS |
|
|
Image Classification (Q)
|
97% |
15216
2.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
15728
255.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
20835
337.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7898
9.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
105676
123.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
202757
237.6 IPS |
|
|
Object Detection (SP)
|
100% |
1795
142.4 IPS |
|
|
Object Detection (HP)
|
100% |
13832
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18743
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3092
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
33755
401.1 IPS |
|
|
Face Detection (Q)
|
100% |
50522
600.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6990
53.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
77952
600.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
127468
996.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20883
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
202864
260.8 IPS |
|
|
Style Transfer (Q)
|
96% |
246733
318.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4923
181.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33885
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
60848
2.25 KIPS |
|
|
Text Classification (SP)
|
100% |
3116
4.16 KIPS |
|
|
Text Classification (HP)
|
100% |
2043
2.73 KIPS |
|
|
Text Classification (Q)
|
93% |
1904
2.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
3062
52.7 IPS |
|
|
Machine Translation (HP)
|
100% |
5950
102.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7315
126.4 IPS |
