iPhone 15 Pro Max
Geekbench AI Score
4016
Single Precision Score
24859
Half Precision Score
34415
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 20 2024 05:18 PM |
| Views | 2 |
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% |
1721
320.0 IPS |
|
|
Image Classification (HP)
|
100% |
11492
2.14 KIPS |
|
|
Image Classification (Q)
|
97% |
15515
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1608
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
12872
208.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
16061
260.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8309
9.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
106401
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
204091
239.2 IPS |
|
|
Object Detection (SP)
|
100% |
1799
142.7 IPS |
|
|
Object Detection (HP)
|
100% |
13673
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19159
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3218
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
33441
397.4 IPS |
|
|
Face Detection (Q)
|
100% |
48961
581.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7227
55.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78697
606.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
126889
992.1 IPS |
|
|
Style Transfer (SP)
|
100% |
21299
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
205873
264.7 IPS |
|
|
Style Transfer (Q)
|
96% |
245230
316.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5039
186.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34523
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59406
2.19 KIPS |
|
|
Text Classification (SP)
|
100% |
3260
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
3305
4.41 KIPS |
|
|
Text Classification (Q)
|
93% |
3590
4.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
3245
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6775
116.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7363
127.2 IPS |
