iPhone 15 Pro Max
Geekbench AI Score
4074
Single Precision Score
24301
Half Precision Score
33428
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 05:46 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1722
320.2 IPS |
|
|
Image Classification (HP)
|
100% |
11087
2.06 KIPS |
|
|
Image Classification (Q)
|
97% |
15223
2.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1608
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
12927
209.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
16014
259.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8822
10.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
106422
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
203811
238.9 IPS |
|
|
Object Detection (SP)
|
100% |
1840
145.9 IPS |
|
|
Object Detection (HP)
|
100% |
13650
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18777
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3228
38.4 IPS |
|
|
Face Detection (HP)
|
100% |
33300
395.7 IPS |
|
|
Face Detection (Q)
|
100% |
49044
582.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7388
56.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78792
607.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
127842
999.5 IPS |
|
|
Style Transfer (SP)
|
100% |
22050
28.3 IPS |
|
|
Style Transfer (HP)
|
100% |
202850
260.8 IPS |
|
|
Style Transfer (Q)
|
96% |
246582
318.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5294
195.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34603
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55939
2.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3235
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
3033
4.05 KIPS |
|
|
Text Classification (Q)
|
93% |
3013
4.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
3113
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6178
106.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7168
123.9 IPS |
