Mac mini (Late 2020)
Geekbench AI Score
3064
Single Precision Score
16146
Half Precision Score
16049
Quantized Score
Geekbench AI 1.4.0 for macOS AArch64
Result Information
| Upload Date | July 10 2025 06:29 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M1 |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| 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 | 3.19 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1372
255.1 IPS |
|
|
Image Classification (HP)
|
100% |
6346
1.18 KIPS |
|
|
Image Classification (Q)
|
96% |
6011
1.12 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1301
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
9759
158.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
10373
168.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6102
7.12 IPS |
|
|
Pose Estimation (HP)
|
100% |
71082
82.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
68398
80.2 IPS |
|
|
Object Detection (SP)
|
100% |
1439
114.1 IPS |
|
|
Object Detection (HP)
|
99% |
7547
600.4 IPS |
|
|
Object Detection (Q)
|
91% |
7064
564.4 IPS |
|
|
Face Detection (SP)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (HP)
|
100% |
16927
201.1 IPS |
|
|
Face Detection (Q)
|
100% |
16199
192.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5404
41.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
50799
391.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
51855
405.2 IPS |
|
|
Style Transfer (SP)
|
100% |
15961
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
124768
160.4 IPS |
|
|
Style Transfer (Q)
|
96% |
119688
154.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3458
127.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
24428
902.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
25640
946.8 IPS |
|
|
Text Classification (SP)
|
100% |
2263
3.02 KIPS |
|
|
Text Classification (HP)
|
100% |
3842
5.13 KIPS |
|
|
Text Classification (Q)
|
93% |
3939
5.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
2428
41.8 IPS |
|
|
Machine Translation (HP)
|
100% |
3601
62.0 IPS |
|
|
Machine Translation (Q)
|
98% |
3706
64.1 IPS |
