iPad16,1
Geekbench AI Score
3779
Single Precision Score
26557
Half Precision Score
36528
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 18 2025 02:57 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| Model | iPad16,1 |
| Model ID | iPad16,1 |
| Motherboard | J410AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1618
300.9 IPS |
|
|
Image Classification (HP)
|
100% |
10549
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
15378
2.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1566
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16711
270.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21591
350.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6715
7.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
102163
119.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
201112
235.7 IPS |
|
|
Object Detection (SP)
|
100% |
1665
132.1 IPS |
|
|
Object Detection (HP)
|
100% |
13641
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
17620
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
3246
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
34609
411.2 IPS |
|
|
Face Detection (Q)
|
100% |
50408
599.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6644
51.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
78117
601.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
122041
954.2 IPS |
|
|
Style Transfer (SP)
|
100% |
19871
25.5 IPS |
|
|
Style Transfer (HP)
|
100% |
207608
266.9 IPS |
|
|
Style Transfer (Q)
|
96% |
250577
323.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4489
165.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34194
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58428
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3227
4.31 KIPS |
|
|
Text Classification (HP)
|
99% |
5581
7.45 KIPS |
|
|
Text Classification (Q)
|
93% |
5657
7.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
3385
58.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6632
114.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7055
121.9 IPS |
