iPhone 15 Pro Max
Geekbench AI Score
3874
Single Precision Score
24487
Half Precision Score
32340
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 18 2024 04:26 AM |
| Views | 1 |
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% |
1634
303.8 IPS |
|
|
Image Classification (HP)
|
100% |
12040
2.24 KIPS |
|
|
Image Classification (Q)
|
97% |
15111
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1593
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
12986
210.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
15960
258.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7483
8.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
106663
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
204171
239.3 IPS |
|
|
Object Detection (SP)
|
100% |
1754
139.1 IPS |
|
|
Object Detection (HP)
|
100% |
13805
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19309
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3153
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
33710
400.5 IPS |
|
|
Face Detection (Q)
|
100% |
49049
582.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7044
54.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78806
607.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
129787
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20746
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
204596
263.0 IPS |
|
|
Style Transfer (Q)
|
96% |
247368
319.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4853
179.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34541
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57490
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3206
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
2893
3.86 KIPS |
|
|
Text Classification (Q)
|
93% |
1899
2.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
3112
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6199
106.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7657
132.3 IPS |
