iPhone 15 Pro Max
Geekbench AI Score
3906
Single Precision Score
24887
Half Precision Score
34653
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 26 2024 06:07 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1703
316.7 IPS |
|
|
Image Classification (HP)
|
100% |
11030
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15126
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1604
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16030
259.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20864
338.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7809
9.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
106480
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
203459
238.5 IPS |
|
|
Object Detection (SP)
|
100% |
1778
141.0 IPS |
|
|
Object Detection (HP)
|
100% |
13551
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18753
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3161
37.6 IPS |
|
|
Face Detection (HP)
|
100% |
33882
402.6 IPS |
|
|
Face Detection (Q)
|
100% |
51063
606.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6938
53.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78024
601.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
128281
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
20495
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
200852
258.2 IPS |
|
|
Style Transfer (Q)
|
96% |
246488
318.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4834
178.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33704
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58004
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3210
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
3007
4.01 KIPS |
|
|
Text Classification (Q)
|
93% |
3099
4.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
3132
53.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6641
114.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7145
123.5 IPS |
