iPhone17,2
Geekbench AI Score
4441
Single Precision Score
33246
Half Precision Score
46148
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | gtimchenko |
| Upload Date | November 15 2024 11:57 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone17,2 |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2003
372.5 IPS |
|
|
Image Classification (HP)
|
100% |
15367
2.86 KIPS |
|
|
Image Classification (Q)
|
97% |
21035
3.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1940
31.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18309
296.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
23720
384.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8640
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
152926
178.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
293762
344.3 IPS |
|
|
Object Detection (SP)
|
100% |
2095
166.2 IPS |
|
|
Object Detection (HP)
|
100% |
16600
1.32 KIPS |
|
|
Object Detection (Q)
|
91% |
22982
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
3355
39.9 IPS |
|
|
Face Detection (HP)
|
100% |
42206
501.5 IPS |
|
|
Face Detection (Q)
|
100% |
58548
695.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7587
58.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
96369
742.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
160864
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
23368
30.0 IPS |
|
|
Style Transfer (HP)
|
100% |
245590
315.7 IPS |
|
|
Style Transfer (Q)
|
96% |
302878
390.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5488
202.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52109
1.92 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84580
3.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3435
4.59 KIPS |
|
|
Text Classification (HP)
|
100% |
4758
6.35 KIPS |
|
|
Text Classification (Q)
|
93% |
4746
6.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3792
65.3 IPS |
|
|
Machine Translation (HP)
|
100% |
9326
160.7 IPS |
|
|
Machine Translation (Q)
|
98% |
11358
196.3 IPS |
