Mac mini (2023)
Geekbench AI Score
3170
Single Precision Score
4772
Half Precision Score
4140
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 09 2024 08:03 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 14.7.1 (Build 23H222) |
| 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 | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1484
275.9 IPS |
|
|
Image Classification (HP)
|
100% |
1859
345.7 IPS |
|
|
Image Classification (Q)
|
96% |
1461
272.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1300
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1271
20.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
1833
29.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6219
7.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
14796
17.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
12735
14.9 IPS |
|
|
Object Detection (SP)
|
100% |
1586
125.8 IPS |
|
|
Object Detection (HP)
|
97% |
2221
176.8 IPS |
|
|
Object Detection (Q)
|
94% |
1690
134.7 IPS |
|
|
Face Detection (SP)
|
100% |
2975
35.4 IPS |
|
|
Face Detection (HP)
|
100% |
4398
52.3 IPS |
|
|
Face Detection (Q)
|
100% |
2883
34.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
5490
42.3 IPS |
|
|
Depth Estimation (HP)
|
97% |
8550
66.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
6499
50.7 IPS |
|
|
Style Transfer (SP)
|
100% |
16898
21.7 IPS |
|
|
Style Transfer (HP)
|
100% |
26750
34.4 IPS |
|
|
Style Transfer (Q)
|
96% |
22324
28.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3817
140.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4722
174.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3633
134.1 IPS |
|
|
Text Classification (SP)
|
100% |
2286
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
3702
4.94 KIPS |
|
|
Text Classification (Q)
|
93% |
3690
4.95 KIPS |
|
|
Machine Translation (SP)
|
100% |
2242
38.6 IPS |
|
|
Machine Translation (HP)
|
98% |
4491
77.6 IPS |
|
|
Machine Translation (Q)
|
98% |
4578
79.1 IPS |
