iPhone 15 Pro Max
Geekbench AI Score
2685
Single Precision Score
13954
Half Precision Score
18363
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 19 2024 08:21 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1424
264.8 IPS |
|
|
Image Classification (HP)
|
100% |
6229
1.16 KIPS |
|
|
Image Classification (Q)
|
97% |
7790
1.45 KIPS |
|
|
Image Segmentation (SP)
|
100% |
798
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
5244
85.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
10497
170.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7301
8.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
87714
102.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
152469
178.7 IPS |
|
|
Object Detection (SP)
|
100% |
1466
116.3 IPS |
|
|
Object Detection (HP)
|
100% |
8386
665.2 IPS |
|
|
Object Detection (Q)
|
93% |
10034
800.7 IPS |
|
|
Face Detection (SP)
|
100% |
2237
26.6 IPS |
|
|
Face Detection (HP)
|
100% |
11224
133.4 IPS |
|
|
Face Detection (Q)
|
100% |
13791
163.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4541
35.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
43055
331.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
64515
504.4 IPS |
|
|
Style Transfer (SP)
|
100% |
12038
15.5 IPS |
|
|
Style Transfer (HP)
|
100% |
127825
164.3 IPS |
|
|
Style Transfer (Q)
|
96% |
137833
177.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3834
141.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18313
676.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27665
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
1800
2.40 KIPS |
|
|
Text Classification (HP)
|
71% |
4072
5.86 KIPS |
|
|
Text Classification (Q)
|
69% |
4056
5.95 KIPS |
|
|
Machine Translation (SP)
|
100% |
1904
32.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2530
43.6 IPS |
|
|
Machine Translation (Q)
|
98% |
2533
43.8 IPS |
