MacBook Pro (16-inch, 2023)
Geekbench AI Score
4177
Single Precision Score
26414
Half Precision Score
29636
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | Brock_Suire |
| Upload Date | November 21 2024 08:35 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C5089c) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,10 |
| Motherboard | Mac14,10 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1391
258.7 IPS |
|
|
Image Classification (HP)
|
100% |
13623
2.53 KIPS |
|
|
Image Classification (Q)
|
96% |
16050
3.00 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1703
27.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
19399
314.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
24583
398.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12940
15.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
105909
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
104233
122.2 IPS |
|
|
Object Detection (SP)
|
100% |
1697
134.6 IPS |
|
|
Object Detection (HP)
|
99% |
15153
1.21 KIPS |
|
|
Object Detection (Q)
|
91% |
16898
1.35 KIPS |
|
|
Face Detection (SP)
|
100% |
3740
44.4 IPS |
|
|
Face Detection (HP)
|
100% |
34903
414.7 IPS |
|
|
Face Detection (Q)
|
100% |
45408
539.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6324
48.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
87228
672.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
108619
848.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24713
31.8 IPS |
|
|
Style Transfer (HP)
|
100% |
203712
261.9 IPS |
|
|
Style Transfer (Q)
|
96% |
195074
251.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5078
187.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40987
1.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48694
1.80 KIPS |
|
|
Text Classification (SP)
|
100% |
2294
3.06 KIPS |
|
|
Text Classification (HP)
|
100% |
3932
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
3824
5.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
4570
78.7 IPS |
|
|
Machine Translation (HP)
|
100% |
3900
67.2 IPS |
|
|
Machine Translation (Q)
|
98% |
4199
72.6 IPS |
