iPhone 14 Pro Max
Geekbench AI Score
2404
Single Precision Score
12882
Half Precision Score
14980
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | RDNewman |
| Upload Date | October 14 2024 09:20 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 14 Pro Max |
| Model ID | iPhone15,3 |
| Motherboard | D74AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1233
229.2 IPS |
|
|
Image Classification (HP)
|
100% |
5573
1.04 KIPS |
|
|
Image Classification (Q)
|
97% |
6204
1.16 KIPS |
|
|
Image Segmentation (SP)
|
100% |
747
12.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5117
82.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
9352
151.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6419
7.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
79356
92.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
85767
100.5 IPS |
|
|
Object Detection (SP)
|
100% |
1335
105.9 IPS |
|
|
Object Detection (HP)
|
100% |
7261
576.0 IPS |
|
|
Object Detection (Q)
|
93% |
8304
662.6 IPS |
|
|
Face Detection (SP)
|
100% |
2261
26.9 IPS |
|
|
Face Detection (HP)
|
100% |
10788
128.2 IPS |
|
|
Face Detection (Q)
|
100% |
12995
154.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4191
32.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
41826
322.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
51478
402.5 IPS |
|
|
Style Transfer (SP)
|
100% |
11336
14.6 IPS |
|
|
Style Transfer (HP)
|
100% |
120750
155.2 IPS |
|
|
Style Transfer (Q)
|
96% |
115057
148.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3342
123.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16404
605.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
20966
774.2 IPS |
|
|
Text Classification (SP)
|
100% |
1379
1.84 KIPS |
|
|
Text Classification (HP)
|
100% |
3596
4.80 KIPS |
|
|
Text Classification (Q)
|
93% |
3571
4.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
1652
28.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2384
41.1 IPS |
|
|
Machine Translation (Q)
|
98% |
2390
41.3 IPS |
