MacBook Pro (16-inch, 2023)
Geekbench AI Score
4105
Single Precision Score
27449
Half Precision Score
30583
Quantized Score
Geekbench AI 1.6.0 for macOS AArch64
Result Information
| User | fo0barorg |
| Upload Date | December 21 2025 06:37 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| 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 | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1382
256.9 IPS |
|
|
Image Classification (HP)
|
100% |
15013
2.79 KIPS |
|
|
Image Classification (Q)
|
96% |
17551
3.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1661
26.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
20142
326.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
24943
404.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
11796
13.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
106299
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
104588
122.6 IPS |
|
|
Object Detection (SP)
|
100% |
1636
129.8 IPS |
|
|
Object Detection (HP)
|
99% |
15399
1.22 KIPS |
|
|
Object Detection (Q)
|
91% |
17077
1.36 KIPS |
|
|
Face Detection (SP)
|
100% |
3650
43.4 IPS |
|
|
Face Detection (HP)
|
100% |
36367
432.1 IPS |
|
|
Face Detection (Q)
|
100% |
47740
567.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6175
47.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
87904
677.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
111950
874.8 IPS |
|
|
Style Transfer (SP)
|
100% |
25601
32.9 IPS |
|
|
Style Transfer (HP)
|
100% |
203348
261.4 IPS |
|
|
Style Transfer (Q)
|
96% |
192865
248.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4958
183.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43429
1.60 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49124
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
2499
3.34 KIPS |
|
|
Text Classification (HP)
|
99% |
4142
5.53 KIPS |
|
|
Text Classification (Q)
|
93% |
4135
5.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
4296
74.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4196
72.3 IPS |
|
|
Machine Translation (Q)
|
98% |
4373
75.6 IPS |
