Mac mini (Late 2020)
Geekbench AI Score
3188
Single Precision Score
5263
Half Precision Score
4372
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | Fritzt |
| Upload Date | March 01 2025 10:01 PM |
| Views | 20 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M1 |
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| Model | Mac mini (Late 2020) |
| Model ID | Macmini9,1 |
| Motherboard | Macmini9,1 |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1375
255.7 IPS |
|
|
Image Classification (HP)
|
100% |
2170
403.5 IPS |
|
|
Image Classification (Q)
|
96% |
1555
290.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1350
21.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2162
35.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2579
41.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6509
7.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
13892
16.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
12033
14.1 IPS |
|
|
Object Detection (SP)
|
100% |
1501
119.1 IPS |
|
|
Object Detection (HP)
|
97% |
2406
191.6 IPS |
|
|
Object Detection (Q)
|
94% |
1779
141.8 IPS |
|
|
Face Detection (SP)
|
100% |
2959
35.2 IPS |
|
|
Face Detection (HP)
|
100% |
5361
63.7 IPS |
|
|
Face Detection (Q)
|
100% |
3160
37.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5795
44.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
11053
85.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
7641
59.7 IPS |
|
|
Style Transfer (SP)
|
100% |
16727
21.5 IPS |
|
|
Style Transfer (HP)
|
100% |
26003
33.4 IPS |
|
|
Style Transfer (Q)
|
96% |
21871
28.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3697
136.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4409
162.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3370
124.4 IPS |
|
|
Text Classification (SP)
|
100% |
2302
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3987
5.32 KIPS |
|
|
Text Classification (Q)
|
93% |
3967
5.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
2456
42.3 IPS |
|
|
Machine Translation (HP)
|
98% |
3844
66.4 IPS |
|
|
Machine Translation (Q)
|
98% |
4213
72.8 IPS |
