iPhone 15 Pro Max
Geekbench AI Score
4963
Single Precision Score
5793
Half Precision Score
5224
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | nadozza |
| Upload Date | September 28 2024 01:16 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| 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% |
2086
387.9 IPS |
|
|
Image Classification (HP)
|
100% |
1755
326.3 IPS |
|
|
Image Classification (Q)
|
97% |
1758
328.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2917
47.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
3950
64.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
4037
65.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
15024
17.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
15864
18.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
13899
16.3 IPS |
|
|
Object Detection (SP)
|
100% |
2570
203.8 IPS |
|
|
Object Detection (HP)
|
100% |
2810
222.9 IPS |
|
|
Object Detection (Q)
|
91% |
2480
198.2 IPS |
|
|
Face Detection (SP)
|
100% |
6451
76.7 IPS |
|
|
Face Detection (HP)
|
100% |
8881
105.5 IPS |
|
|
Face Detection (Q)
|
100% |
6233
74.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
11684
90.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
12814
98.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
10803
84.4 IPS |
|
|
Style Transfer (SP)
|
100% |
28703
36.9 IPS |
|
|
Style Transfer (HP)
|
100% |
34673
44.6 IPS |
|
|
Style Transfer (Q)
|
96% |
33663
43.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6422
237.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6621
244.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5428
200.4 IPS |
|
|
Text Classification (SP)
|
100% |
3204
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
5511
7.36 KIPS |
|
|
Text Classification (Q)
|
93% |
5461
7.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
868
15.0 IPS |
|
|
Machine Translation (HP)
|
100% |
958
16.5 IPS |
|
|
Machine Translation (Q)
|
98% |
921
15.9 IPS |
