Mac mini (Late 2020)
Geekbench AI Score
4946
Single Precision Score
5816
Half Precision Score
5133
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | Fritzt |
| Upload Date | March 01 2025 10:06 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| 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% |
2496
464.1 IPS |
|
|
Image Classification (HP)
|
100% |
2530
470.6 IPS |
|
|
Image Classification (Q)
|
97% |
2263
422.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2652
43.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
3642
59.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3714
60.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
16764
19.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
18508
21.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
17045
20.0 IPS |
|
|
Object Detection (SP)
|
100% |
2675
212.2 IPS |
|
|
Object Detection (HP)
|
100% |
2746
217.9 IPS |
|
|
Object Detection (Q)
|
91% |
2253
180.0 IPS |
|
|
Face Detection (SP)
|
100% |
6732
80.0 IPS |
|
|
Face Detection (HP)
|
100% |
8138
96.7 IPS |
|
|
Face Detection (Q)
|
100% |
5625
66.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
12048
92.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
13685
105.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
11405
89.2 IPS |
|
|
Style Transfer (SP)
|
100% |
28602
36.8 IPS |
|
|
Style Transfer (HP)
|
100% |
34492
44.3 IPS |
|
|
Style Transfer (Q)
|
96% |
32206
41.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6396
236.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7129
263.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5524
204.0 IPS |
|
|
Text Classification (SP)
|
100% |
2297
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3984
5.32 KIPS |
|
|
Text Classification (Q)
|
93% |
3971
5.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
866
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
867
14.9 IPS |
|
|
Machine Translation (Q)
|
98% |
869
15.0 IPS |
