iPhone17,2
Geekbench AI Score
4435
Single Precision Score
32554
Half Precision Score
44868
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | vdacquel |
| Upload Date | September 23 2024 02:10 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone17,2 |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.03 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1993
370.6 IPS |
|
|
Image Classification (HP)
|
100% |
15287
2.84 KIPS |
|
|
Image Classification (Q)
|
97% |
20907
3.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1942
31.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
14659
237.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
18261
296.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8910
10.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
154120
179.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
292915
343.3 IPS |
|
|
Object Detection (SP)
|
100% |
2091
165.9 IPS |
|
|
Object Detection (HP)
|
100% |
16582
1.32 KIPS |
|
|
Object Detection (Q)
|
91% |
22550
1.80 KIPS |
|
|
Face Detection (SP)
|
100% |
3482
41.4 IPS |
|
|
Face Detection (HP)
|
100% |
41153
489.0 IPS |
|
|
Face Detection (Q)
|
100% |
55511
659.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7437
57.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
95563
736.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
162623
1.27 KIPS |
|
|
Style Transfer (SP)
|
100% |
23311
30.0 IPS |
|
|
Style Transfer (HP)
|
100% |
246069
316.3 IPS |
|
|
Style Transfer (Q)
|
96% |
303006
391.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5492
202.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51105
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
87490
3.23 KIPS |
|
|
Text Classification (SP)
|
100% |
3422
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
4716
6.30 KIPS |
|
|
Text Classification (Q)
|
93% |
4793
6.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
3599
62.0 IPS |
|
|
Machine Translation (HP)
|
100% |
10009
172.4 IPS |
|
|
Machine Translation (Q)
|
98% |
11433
197.6 IPS |
