iPhone 15 Pro Max
Geekbench AI Score
3799
Single Precision Score
23499
Half Precision Score
33195
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 11 2024 01:45 AM |
| Views | 2 |
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% |
1613
300.0 IPS |
|
|
Image Classification (HP)
|
100% |
11016
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15191
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1570
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
15514
251.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
20691
335.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7352
8.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
102745
119.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
201849
236.6 IPS |
|
|
Object Detection (SP)
|
100% |
1743
138.3 IPS |
|
|
Object Detection (HP)
|
100% |
13766
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18675
1.49 KIPS |
|
|
Face Detection (SP)
|
100% |
3044
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
33497
398.0 IPS |
|
|
Face Detection (Q)
|
100% |
51161
607.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6868
52.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78045
601.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
128433
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
19850
25.5 IPS |
|
|
Style Transfer (HP)
|
100% |
201870
259.5 IPS |
|
|
Style Transfer (Q)
|
96% |
248412
320.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4675
172.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34480
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59553
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3196
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
1920
2.56 KIPS |
|
|
Text Classification (Q)
|
93% |
1879
2.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
3115
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6080
104.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7509
129.8 IPS |
