Mac mini (2023)
Geekbench ML Score
4969
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 06:42 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | Mac mini (2023) |
| Model ID | Mac14,3 |
| Motherboard | Mac14,3 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.48 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% |
3464
648.2 IPS |
|
|
Image Classification (F16)
|
100% |
3511
656.9 IPS |
|
|
Image Classification (I8)
|
99% |
3132
586.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1352
22.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1430
23.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1433
23.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
22949
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
25124
30.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
24543
29.7 IPS |
|
|
Object Detection (F32)
|
100% |
2203
164.4 IPS |
|
|
Object Detection (F16)
|
100% |
2932
218.9 IPS |
|
|
Object Detection (I8)
|
97% |
2556
190.8 IPS |
|
|
Face Detection (F32)
|
100% |
9191
109.3 IPS |
|
|
Face Detection (F16)
|
98% |
10609
126.1 IPS |
|
|
Face Detection (I8)
|
97% |
10186
121.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
16218
125.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
17654
136.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
16198
125.6 IPS |
|
|
Style Transfer (F32)
|
100% |
40365
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
47256
62.2 IPS |
|
|
Style Transfer (I8)
|
100% |
46822
61.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8010
286.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8684
310.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
8256
294.9 IPS |
|
|
Text Classification (F32)
|
100% |
637
915.7 IPS |
|
|
Text Classification (F16)
|
100% |
520
747.7 IPS |
|
|
Text Classification (I8)
|
96% |
558
801.7 IPS |
|
|
Machine Translation (F32)
|
100% |
895
16.5 IPS |
|
|
Machine Translation (F16)
|
100% |
932
17.1 IPS |
|
|
Machine Translation (I8)
|
99% |
864
15.9 IPS |
