Mac mini (2023)
Geekbench AI Score
4154
Single Precision Score
6748
Half Precision Score
5297
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 17 2024 07:16 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1390
258.4 IPS |
|
|
Image Classification (HP)
|
100% |
2272
422.5 IPS |
|
|
Image Classification (Q)
|
96% |
1666
311.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1692
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2544
41.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2926
47.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
12627
14.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
24926
29.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
19008
22.3 IPS |
|
|
Object Detection (SP)
|
100% |
1690
134.1 IPS |
|
|
Object Detection (HP)
|
97% |
2729
217.3 IPS |
|
|
Object Detection (Q)
|
94% |
1982
158.0 IPS |
|
|
Face Detection (SP)
|
100% |
3639
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
5858
69.6 IPS |
|
|
Face Detection (Q)
|
100% |
3404
40.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6381
49.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
12298
95.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8243
64.4 IPS |
|
|
Style Transfer (SP)
|
100% |
25117
32.3 IPS |
|
|
Style Transfer (HP)
|
100% |
39531
50.8 IPS |
|
|
Style Transfer (Q)
|
96% |
29588
38.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5149
190.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6951
256.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4423
163.3 IPS |
|
|
Text Classification (SP)
|
100% |
2280
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
4002
5.34 KIPS |
|
|
Text Classification (Q)
|
93% |
3968
5.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
4454
76.7 IPS |
|
|
Machine Translation (HP)
|
98% |
6292
108.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6506
112.4 IPS |
