iPhone 15 Pro Max
Geekbench AI Score
4026
Single Precision Score
24236
Half Precision Score
32584
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 18 2024 01:54 AM |
| 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% |
1724
320.6 IPS |
|
|
Image Classification (HP)
|
100% |
10610
1.97 KIPS |
|
|
Image Classification (Q)
|
97% |
15202
2.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1589
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
12853
208.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
15963
258.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
8509
9.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
106409
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
202996
237.9 IPS |
|
|
Object Detection (SP)
|
100% |
1826
144.8 IPS |
|
|
Object Detection (HP)
|
100% |
13476
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18940
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3213
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
34536
410.4 IPS |
|
|
Face Detection (Q)
|
100% |
49358
586.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
7273
56.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
78780
607.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
129121
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
22135
28.5 IPS |
|
|
Style Transfer (HP)
|
100% |
205368
264.0 IPS |
|
|
Style Transfer (Q)
|
96% |
250548
323.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5160
190.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34106
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56731
2.09 KIPS |
|
|
Text Classification (SP)
|
100% |
3182
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
3064
4.09 KIPS |
|
|
Text Classification (Q)
|
93% |
2240
3.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
3101
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6125
105.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7127
123.2 IPS |
