iPhone 15 Pro Max
Geekbench AI Score
3951
Single Precision Score
24303
Half Precision Score
33589
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 18 2024 07:48 AM |
| Views | 1 |
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% |
1688
313.9 IPS |
|
|
Image Classification (HP)
|
100% |
10948
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
15246
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1611
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
12988
210.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
15992
259.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8054
9.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
106691
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
202878
237.8 IPS |
|
|
Object Detection (SP)
|
100% |
1785
141.6 IPS |
|
|
Object Detection (HP)
|
100% |
13458
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18815
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3150
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
34440
409.2 IPS |
|
|
Face Detection (Q)
|
100% |
48976
581.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7113
54.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78503
604.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
128390
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21264
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
204301
262.6 IPS |
|
|
Style Transfer (Q)
|
96% |
245712
317.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5037
186.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34513
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55930
2.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3184
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
3021
4.03 KIPS |
|
|
Text Classification (Q)
|
93% |
3018
4.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
3107
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6115
105.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7532
130.2 IPS |
