iPhone 16 Pro
Geekbench AI Score
4238
Single Precision Score
33491
Half Precision Score
47110
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | xtoofur |
| Upload Date | December 24 2024 02:11 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 16 Pro |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1958
364.1 IPS |
|
|
Image Classification (HP)
|
100% |
15784
2.94 KIPS |
|
|
Image Classification (Q)
|
97% |
22023
4.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1914
31.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
18325
297.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
24239
392.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7509
8.76 IPS |
|
|
Pose Estimation (HP)
|
100% |
138565
161.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
295929
346.8 IPS |
|
|
Object Detection (SP)
|
100% |
2012
159.6 IPS |
|
|
Object Detection (HP)
|
100% |
16768
1.33 KIPS |
|
|
Object Detection (Q)
|
91% |
23314
1.86 KIPS |
|
|
Face Detection (SP)
|
100% |
3453
41.0 IPS |
|
|
Face Detection (HP)
|
100% |
41688
495.3 IPS |
|
|
Face Detection (Q)
|
100% |
60558
719.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7086
54.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
96069
740.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
165670
1.30 KIPS |
|
|
Style Transfer (SP)
|
100% |
20610
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
244864
314.8 IPS |
|
|
Style Transfer (Q)
|
96% |
304941
393.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5069
187.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52435
1.94 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
86457
3.19 KIPS |
|
|
Text Classification (SP)
|
100% |
3495
4.66 KIPS |
|
|
Text Classification (HP)
|
100% |
4922
6.57 KIPS |
|
|
Text Classification (Q)
|
93% |
4702
6.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
3700
63.7 IPS |
|
|
Machine Translation (HP)
|
100% |
10438
179.8 IPS |
|
|
Machine Translation (Q)
|
98% |
11757
203.2 IPS |
