Mac mini (2023)
Geekbench ML Score
4943
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 26 2024 08:26 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4 (Build 23E214) |
| 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3418
639.7 IPS |
|
|
Image Classification (F16)
|
100% |
3438
643.3 IPS |
|
|
Image Classification (I8)
|
99% |
3038
568.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1434
23.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1487
24.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1451
24.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
22740
27.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
24471
29.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
24241
29.4 IPS |
|
|
Object Detection (F32)
|
100% |
2552
190.5 IPS |
|
|
Object Detection (F16)
|
100% |
2881
215.1 IPS |
|
|
Object Detection (I8)
|
97% |
2378
177.6 IPS |
|
|
Face Detection (F32)
|
100% |
9177
109.1 IPS |
|
|
Face Detection (F16)
|
98% |
10750
127.8 IPS |
|
|
Face Detection (I8)
|
97% |
10155
120.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16068
124.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
17260
133.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
15838
122.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40340
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
46927
61.7 IPS |
|
|
Style Transfer (I8)
|
100% |
46756
61.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8025
286.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8435
301.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7996
285.6 IPS |
|
|
Text Classification (F32)
|
100% |
508
730.0 IPS |
|
|
Text Classification (F16)
|
100% |
579
832.2 IPS |
|
|
Text Classification (I8)
|
96% |
579
831.7 IPS |
|
|
Machine Translation (F32)
|
100% |
892
16.4 IPS |
|
|
Machine Translation (F16)
|
100% |
927
17.1 IPS |
|
|
Machine Translation (I8)
|
99% |
855
15.7 IPS |
