Mac mini (2023)
Geekbench AI Score
3148
Single Precision Score
26172
Half Precision Score
28498
Quantized Score
Geekbench AI 1.6.0 for macOS AArch64
Result Information
| Upload Date | February 01 2026 02:53 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| 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 | 3.21 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1212
225.5 IPS |
|
|
Image Classification (HP)
|
100% |
14061
2.61 KIPS |
|
|
Image Classification (Q)
|
96% |
16202
3.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1446
23.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
19518
316.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
23896
387.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5942
6.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
96160
112.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
97894
114.7 IPS |
|
|
Object Detection (SP)
|
100% |
1288
102.2 IPS |
|
|
Object Detection (HP)
|
99% |
14935
1.19 KIPS |
|
|
Object Detection (Q)
|
91% |
15820
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
2748
32.6 IPS |
|
|
Face Detection (HP)
|
100% |
34458
409.4 IPS |
|
|
Face Detection (Q)
|
100% |
43232
513.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5434
41.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
82814
638.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
96265
752.3 IPS |
|
|
Style Transfer (SP)
|
100% |
17407
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
206793
265.8 IPS |
|
|
Style Transfer (Q)
|
96% |
181830
234.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3591
132.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43009
1.59 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49495
1.83 KIPS |
|
|
Text Classification (SP)
|
100% |
2345
3.13 KIPS |
|
|
Text Classification (HP)
|
99% |
3786
5.05 KIPS |
|
|
Text Classification (Q)
|
93% |
3746
5.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
3260
56.2 IPS |
|
|
Machine Translation (HP)
|
100% |
3983
68.6 IPS |
|
|
Machine Translation (Q)
|
98% |
4200
72.6 IPS |
