iPhone 13 Pro Max
Geekbench AI Score
3203
Single Precision Score
19427
Half Precision Score
22287
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 31 2024 03:32 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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 | 5.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1331
247.4 IPS |
|
|
Image Classification (HP)
|
100% |
8127
1.51 KIPS |
|
|
Image Classification (Q)
|
96% |
10386
1.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1251
20.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12279
199.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
13393
217.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6073
7.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
87645
102.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
93642
109.8 IPS |
|
|
Object Detection (SP)
|
100% |
1410
111.8 IPS |
|
|
Object Detection (HP)
|
99% |
10885
865.9 IPS |
|
|
Object Detection (Q)
|
91% |
12211
975.7 IPS |
|
|
Face Detection (SP)
|
100% |
2646
31.4 IPS |
|
|
Face Detection (HP)
|
100% |
25986
308.8 IPS |
|
|
Face Detection (Q)
|
100% |
34075
404.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5315
40.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
52130
401.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
71708
560.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17237
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
154892
199.1 IPS |
|
|
Style Transfer (Q)
|
96% |
158622
204.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3953
146.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28837
1.06 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
29227
1.08 KIPS |
|
|
Text Classification (SP)
|
100% |
2454
3.28 KIPS |
|
|
Text Classification (HP)
|
100% |
2150
2.87 KIPS |
|
|
Text Classification (Q)
|
93% |
2388
3.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3394
58.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6183
106.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7029
121.5 IPS |
