iPhone 13 Pro Max
Geekbench AI Score
2156
Single Precision Score
10667
Half Precision Score
12068
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | ElementalOwl |
| Upload Date | September 17 2024 07:56 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.7 |
| Model | iPhone 13 Pro Max |
| Model ID | iPhone14,3 |
| Motherboard | D64AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1187
220.8 IPS |
|
|
Image Classification (HP)
|
100% |
4418
821.6 IPS |
|
|
Image Classification (Q)
|
96% |
4910
916.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
648
10.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
3931
63.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
5968
96.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5626
6.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
70265
82.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
77915
91.3 IPS |
|
|
Object Detection (SP)
|
100% |
1195
94.8 IPS |
|
|
Object Detection (HP)
|
99% |
5543
440.9 IPS |
|
|
Object Detection (Q)
|
93% |
6868
548.0 IPS |
|
|
Face Detection (SP)
|
100% |
1873
22.3 IPS |
|
|
Face Detection (HP)
|
100% |
10582
125.7 IPS |
|
|
Face Detection (Q)
|
100% |
12316
146.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
3667
28.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
34768
267.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
40338
315.2 IPS |
|
|
Style Transfer (SP)
|
100% |
10125
13.0 IPS |
|
|
Style Transfer (HP)
|
100% |
102179
131.4 IPS |
|
|
Style Transfer (Q)
|
95% |
102420
132.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3032
112.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13230
488.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
14866
548.9 IPS |
|
|
Text Classification (SP)
|
100% |
1297
1.73 KIPS |
|
|
Text Classification (HP)
|
100% |
2637
3.52 KIPS |
|
|
Text Classification (Q)
|
93% |
2561
3.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
1535
26.4 IPS |
|
|
Machine Translation (HP)
|
100% |
2150
37.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2157
37.3 IPS |
