Mac mini (Late 2020)
Geekbench AI Score
3143
Single Precision Score
5269
Half Precision Score
4368
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | tjticknor |
| Upload Date | April 17 2025 08:40 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M1 |
| System Information | |
|---|---|
| Operating System | macOS 15.4.1 (Build 24E263) |
| 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 | 3.18 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1379
256.4 IPS |
|
|
Image Classification (HP)
|
100% |
2167
403.0 IPS |
|
|
Image Classification (Q)
|
96% |
1550
289.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1332
21.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2152
34.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
2508
40.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6393
7.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
13990
16.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
11963
14.0 IPS |
|
|
Object Detection (SP)
|
100% |
1482
117.6 IPS |
|
|
Object Detection (HP)
|
97% |
2354
187.4 IPS |
|
|
Object Detection (Q)
|
94% |
1770
141.1 IPS |
|
|
Face Detection (SP)
|
100% |
2863
34.0 IPS |
|
|
Face Detection (HP)
|
100% |
5180
61.5 IPS |
|
|
Face Detection (Q)
|
100% |
3079
36.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5526
42.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
10265
79.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
7329
57.3 IPS |
|
|
Style Transfer (SP)
|
100% |
16590
21.3 IPS |
|
|
Style Transfer (HP)
|
100% |
26555
34.1 IPS |
|
|
Style Transfer (Q)
|
96% |
22093
28.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3642
134.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4627
170.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3414
126.1 IPS |
|
|
Text Classification (SP)
|
100% |
2328
3.11 KIPS |
|
|
Text Classification (HP)
|
100% |
4094
5.46 KIPS |
|
|
Text Classification (Q)
|
93% |
4066
5.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
2429
41.8 IPS |
|
|
Machine Translation (HP)
|
98% |
4020
69.5 IPS |
|
|
Machine Translation (Q)
|
98% |
4439
76.7 IPS |
