Mac mini (Late 2020)
Geekbench ML Score
3004
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 05:45 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1295
242.4 IPS |
|
|
Image Classification (F16)
|
100% |
1673
313.1 IPS |
|
|
Image Classification (I8)
|
99% |
1668
312.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
589
9.84 IPS |
|
|
Image Segmentation (F16)
|
100% |
585
9.78 IPS |
|
|
Image Segmentation (I8)
|
100% |
587
9.81 IPS |
|
|
Pose Estimation (F32)
|
100% |
5641
6.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
13002
15.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
12984
15.7 IPS |
|
|
Object Detection (F32)
|
100% |
1320
98.6 IPS |
|
|
Object Detection (F16)
|
100% |
1754
130.9 IPS |
|
|
Object Detection (I8)
|
97% |
1320
98.5 IPS |
|
|
Face Detection (F32)
|
100% |
2401
28.5 IPS |
|
|
Face Detection (F16)
|
97% |
3980
47.3 IPS |
|
|
Face Detection (I8)
|
97% |
3947
46.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
5204
40.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
8159
63.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
8165
63.3 IPS |
|
|
Style Transfer (F32)
|
100% |
15301
20.1 IPS |
|
|
Style Transfer (F16)
|
100% |
24142
31.8 IPS |
|
|
Style Transfer (I8)
|
100% |
24616
32.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3486
124.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4809
171.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4574
163.4 IPS |
|
|
Text Classification (F32)
|
100% |
2103
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3417
4.91 KIPS |
|
|
Text Classification (I8)
|
96% |
3367
4.84 KIPS |
|
|
Machine Translation (F32)
|
100% |
726
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
875
16.1 IPS |
|
|
Machine Translation (I8)
|
99% |
719
13.2 IPS |
