iPhone 15 Pro Max
Geekbench AI Score
4024
Single Precision Score
24774
Half Precision Score
34625
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 09 2024 06:22 PM |
| Views | 1 |
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% |
1717
319.4 IPS |
|
|
Image Classification (HP)
|
100% |
10818
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15079
2.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1675
27.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
15696
254.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
20892
338.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8305
9.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
107909
125.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
205015
240.3 IPS |
|
|
Object Detection (SP)
|
100% |
1817
144.1 IPS |
|
|
Object Detection (HP)
|
100% |
13666
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19032
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3237
38.5 IPS |
|
|
Face Detection (HP)
|
100% |
34304
407.6 IPS |
|
|
Face Detection (Q)
|
100% |
50051
594.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7258
55.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78965
608.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
129885
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
21665
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
202428
260.2 IPS |
|
|
Style Transfer (Q)
|
96% |
248033
320.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5113
188.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34007
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55394
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3190
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3049
4.07 KIPS |
|
|
Text Classification (Q)
|
93% |
3088
4.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
3094
53.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6118
105.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7307
126.3 IPS |
