Mac mini (Late 2020)
Geekbench ML Score
3532
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | WrigleyBeard |
| Upload Date | August 17 2024 01:41 AM |
| Views | 4 |
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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1700
318.2 IPS |
|
|
Image Classification (F16)
|
100% |
1703
318.6 IPS |
|
|
Image Classification (I8)
|
99% |
1693
316.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
839
14.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
926
15.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
907
15.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
16612
20.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
18135
22.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
17788
21.5 IPS |
|
|
Object Detection (F32)
|
100% |
1512
112.9 IPS |
|
|
Object Detection (F16)
|
100% |
1480
110.5 IPS |
|
|
Object Detection (I8)
|
97% |
1500
112.0 IPS |
|
|
Face Detection (F32)
|
100% |
6127
72.9 IPS |
|
|
Face Detection (F16)
|
98% |
7390
87.9 IPS |
|
|
Face Detection (I8)
|
97% |
6905
82.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12427
96.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
13790
106.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
12541
97.3 IPS |
|
|
Style Transfer (F32)
|
100% |
27588
36.3 IPS |
|
|
Style Transfer (F16)
|
100% |
32394
42.6 IPS |
|
|
Style Transfer (I8)
|
100% |
32267
42.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5644
201.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5991
214.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5911
211.1 IPS |
|
|
Text Classification (F32)
|
100% |
996
1.43 KIPS |
|
|
Text Classification (F16)
|
100% |
714
1.03 KIPS |
|
|
Text Classification (I8)
|
96% |
514
739.3 IPS |
|
|
Machine Translation (F32)
|
100% |
679
12.5 IPS |
|
|
Machine Translation (F16)
|
100% |
709
13.0 IPS |
|
|
Machine Translation (I8)
|
99% |
656
12.1 IPS |
