iPhone 15 Pro Max
Geekbench AI Score
3985
Single Precision Score
25230
Half Precision Score
34848
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 11 2024 01:39 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1694
315.0 IPS |
|
|
Image Classification (HP)
|
100% |
11185
2.08 KIPS |
|
|
Image Classification (Q)
|
97% |
14733
2.75 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1622
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15791
256.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
20741
336.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8183
9.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
106415
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
205994
241.4 IPS |
|
|
Object Detection (SP)
|
100% |
1799
142.7 IPS |
|
|
Object Detection (HP)
|
100% |
13778
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18997
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3162
37.6 IPS |
|
|
Face Detection (HP)
|
100% |
35519
422.0 IPS |
|
|
Face Detection (Q)
|
100% |
51006
606.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7208
55.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78588
605.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
129116
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21499
27.6 IPS |
|
|
Style Transfer (HP)
|
100% |
205062
263.6 IPS |
|
|
Style Transfer (Q)
|
96% |
246332
317.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5082
187.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33820
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57508
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3296
4.40 KIPS |
|
|
Text Classification (Q)
|
93% |
3269
4.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
3128
53.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6327
109.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7243
125.2 IPS |
