iPhone 14 Pro Max
Geekbench AI Score
2392
Single Precision Score
12878
Half Precision Score
14827
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | RDNewman |
| Upload Date | October 16 2024 01:20 AM |
| Views | 9 |
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% |
1214
225.7 IPS |
|
|
Image Classification (HP)
|
100% |
5954
1.11 KIPS |
|
|
Image Classification (Q)
|
97% |
6300
1.18 KIPS |
|
|
Image Segmentation (SP)
|
100% |
744
12.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5003
81.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
8997
145.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6456
7.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
81411
95.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
87089
102.1 IPS |
|
|
Object Detection (SP)
|
100% |
1333
105.7 IPS |
|
|
Object Detection (HP)
|
100% |
7055
559.6 IPS |
|
|
Object Detection (Q)
|
93% |
8208
655.0 IPS |
|
|
Face Detection (SP)
|
100% |
2193
26.1 IPS |
|
|
Face Detection (HP)
|
100% |
10706
127.2 IPS |
|
|
Face Detection (Q)
|
100% |
12763
151.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4214
32.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
39847
307.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
49874
389.9 IPS |
|
|
Style Transfer (SP)
|
100% |
11371
14.6 IPS |
|
|
Style Transfer (HP)
|
100% |
120425
154.8 IPS |
|
|
Style Transfer (Q)
|
96% |
115812
149.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3312
122.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16886
623.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
20749
766.2 IPS |
|
|
Text Classification (SP)
|
100% |
1378
1.84 KIPS |
|
|
Text Classification (HP)
|
100% |
3488
4.66 KIPS |
|
|
Text Classification (Q)
|
93% |
3540
4.75 KIPS |
|
|
Machine Translation (SP)
|
100% |
1645
28.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2424
41.8 IPS |
|
|
Machine Translation (Q)
|
98% |
2342
40.5 IPS |
