iPhone 13 Pro Max
Geekbench AI Score
3283
Single Precision Score
16663
Half Precision Score
18160
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 05:23 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1352
251.4 IPS |
|
|
Image Classification (HP)
|
100% |
8967
1.67 KIPS |
|
|
Image Classification (Q)
|
96% |
9648
1.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1306
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
6918
112.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
7419
120.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
6417
7.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
85375
99.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
93815
110.0 IPS |
|
|
Object Detection (SP)
|
100% |
1465
116.2 IPS |
|
|
Object Detection (HP)
|
99% |
10454
831.6 IPS |
|
|
Object Detection (Q)
|
91% |
11696
934.6 IPS |
|
|
Face Detection (SP)
|
100% |
2713
32.2 IPS |
|
|
Face Detection (HP)
|
100% |
26902
319.7 IPS |
|
|
Face Detection (Q)
|
100% |
32080
381.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5519
42.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
52581
405.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
70918
554.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17740
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
155933
200.5 IPS |
|
|
Style Transfer (Q)
|
96% |
150311
194.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3954
146.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26658
984.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27960
1.03 KIPS |
|
|
Text Classification (SP)
|
100% |
2423
3.23 KIPS |
|
|
Text Classification (HP)
|
100% |
2287
3.05 KIPS |
|
|
Text Classification (Q)
|
93% |
2358
3.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
3445
59.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2217
38.2 IPS |
|
|
Machine Translation (Q)
|
98% |
2204
38.1 IPS |
