Mac mini (2023)
Geekbench AI Score
6866
Single Precision Score
7753
Half Precision Score
6748
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | StanH |
| Upload Date | March 09 2025 02:33 AM |
| Views | 27 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| 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 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3673
683.1 IPS |
|
|
Image Classification (HP)
|
100% |
3732
694.0 IPS |
|
|
Image Classification (Q)
|
97% |
3110
580.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
4059
65.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
5047
81.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
5105
82.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
24695
28.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
26319
30.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
24490
28.7 IPS |
|
|
Object Detection (SP)
|
100% |
3515
278.8 IPS |
|
|
Object Detection (HP)
|
100% |
3718
294.9 IPS |
|
|
Object Detection (Q)
|
91% |
3072
245.5 IPS |
|
|
Face Detection (SP)
|
100% |
10369
123.2 IPS |
|
|
Face Detection (HP)
|
100% |
12165
144.5 IPS |
|
|
Face Detection (Q)
|
100% |
8414
100.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
16861
129.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
18157
139.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
15024
117.4 IPS |
|
|
Style Transfer (SP)
|
100% |
43044
55.3 IPS |
|
|
Style Transfer (HP)
|
100% |
49033
63.0 IPS |
|
|
Style Transfer (Q)
|
96% |
45548
58.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10447
385.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
11244
415.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8229
303.9 IPS |
|
|
Text Classification (SP)
|
100% |
2285
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
3809
5.08 KIPS |
|
|
Text Classification (Q)
|
93% |
3747
5.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
1002
17.3 IPS |
|
|
Machine Translation (HP)
|
100% |
918
15.8 IPS |
|
|
Machine Translation (Q)
|
98% |
924
16.0 IPS |
