Mac mini (2023)
Geekbench AI Score
4092
Single Precision Score
6680
Half Precision Score
5669
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | kfendt |
| Upload Date | February 27 2025 06:27 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1386
257.8 IPS |
|
|
Image Classification (HP)
|
100% |
2265
421.2 IPS |
|
|
Image Classification (Q)
|
99% |
2261
421.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1702
27.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2543
41.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
2524
40.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
12591
14.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
25127
29.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
18251
21.4 IPS |
|
|
Object Detection (SP)
|
100% |
1674
132.8 IPS |
|
|
Object Detection (HP)
|
97% |
2698
214.8 IPS |
|
|
Object Detection (Q)
|
94% |
1969
157.0 IPS |
|
|
Face Detection (SP)
|
100% |
3488
41.4 IPS |
|
|
Face Detection (HP)
|
100% |
5565
66.1 IPS |
|
|
Face Detection (Q)
|
100% |
3372
40.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6262
48.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
12067
93.2 IPS |
|
|
Depth Estimation (Q)
|
97% |
11952
92.4 IPS |
|
|
Style Transfer (SP)
|
100% |
24850
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38255
49.2 IPS |
|
|
Style Transfer (Q)
|
100% |
38786
49.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5088
187.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7019
259.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
4364
161.7 IPS |
|
|
Text Classification (SP)
|
100% |
2276
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
4027
5.38 KIPS |
|
|
Text Classification (Q)
|
93% |
3969
5.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
4217
72.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6246
107.9 IPS |
|
|
Machine Translation (Q)
|
98% |
6179
106.8 IPS |
