Mac mini (2023)
Geekbench AI Score
3466
Single Precision Score
27137
Half Precision Score
30098
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| Upload Date | September 13 2025 01:07 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.6.1 (Build 24G90) |
| 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 | 3.49 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1394
259.3 IPS |
|
|
Image Classification (HP)
|
100% |
15325
2.85 KIPS |
|
|
Image Classification (Q)
|
96% |
15745
2.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1496
24.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
19287
312.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23697
384.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6840
7.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
106126
123.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
105500
123.7 IPS |
|
|
Object Detection (SP)
|
100% |
1538
122.0 IPS |
|
|
Object Detection (HP)
|
99% |
15789
1.26 KIPS |
|
|
Object Detection (Q)
|
91% |
18338
1.47 KIPS |
|
|
Face Detection (SP)
|
100% |
3020
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
33726
400.7 IPS |
|
|
Face Detection (Q)
|
100% |
42962
510.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5573
42.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
87937
677.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
110963
867.1 IPS |
|
|
Style Transfer (SP)
|
100% |
18719
24.1 IPS |
|
|
Style Transfer (HP)
|
100% |
203608
261.7 IPS |
|
|
Style Transfer (Q)
|
96% |
194201
250.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4059
149.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40995
1.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
50667
1.87 KIPS |
|
|
Text Classification (SP)
|
100% |
2367
3.16 KIPS |
|
|
Text Classification (HP)
|
100% |
4016
5.36 KIPS |
|
|
Text Classification (Q)
|
93% |
3989
5.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
3773
65.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4400
75.8 IPS |
|
|
Machine Translation (Q)
|
98% |
4517
78.1 IPS |
