Mac mini (2023)
Geekbench ML Score
5133
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 05:38 PM |
| Views | 1 |
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% |
3423
640.6 IPS |
|
|
Image Classification (F16)
|
100% |
3583
670.5 IPS |
|
|
Image Classification (I8)
|
99% |
3075
575.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1462
24.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1528
25.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1546
25.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
23617
28.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
24980
30.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
24409
29.6 IPS |
|
|
Object Detection (F32)
|
100% |
2874
214.5 IPS |
|
|
Object Detection (F16)
|
100% |
2942
219.7 IPS |
|
|
Object Detection (I8)
|
97% |
2681
200.1 IPS |
|
|
Face Detection (F32)
|
100% |
9356
111.2 IPS |
|
|
Face Detection (F16)
|
98% |
10719
127.5 IPS |
|
|
Face Detection (I8)
|
97% |
10193
121.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
16373
127.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
17491
135.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
16042
124.4 IPS |
|
|
Style Transfer (F32)
|
100% |
41278
54.3 IPS |
|
|
Style Transfer (F16)
|
100% |
44715
58.8 IPS |
|
|
Style Transfer (I8)
|
100% |
46502
61.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8850
316.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
9127
325.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
8798
314.2 IPS |
|
|
Text Classification (F32)
|
100% |
643
924.3 IPS |
|
|
Text Classification (F16)
|
100% |
562
808.3 IPS |
|
|
Text Classification (I8)
|
96% |
563
808.8 IPS |
|
|
Machine Translation (F32)
|
100% |
953
17.5 IPS |
|
|
Machine Translation (F16)
|
100% |
978
18.0 IPS |
|
|
Machine Translation (I8)
|
99% |
887
16.3 IPS |
