MacBook Pro (16-inch Late 2019)
Geekbench AI Score
890
Single Precision Score
111
Half Precision Score
89
Quantized Score
Geekbench AI 1.4.0 for macOS AVX2
Result Information
| User | AdamOp |
| Upload Date | September 04 2025 01:24 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Intel Core i7-9750H |
| System Information | |
|---|---|
| Operating System | macOS 15.6.1 (Build 24G90) |
| Model | MacBook Pro (16-inch Late 2019) |
| Model ID | MacBookPro16,1 |
| Motherboard | Apple Inc. Mac-E1008331FDC96864 MacBookPro16,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-9750H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
432
80.4 IPS |
|
|
Image Classification (HP)
|
0
|
||
|
Image Classification (Q)
|
0
|
||
|
Image Segmentation (SP)
|
100% |
409
6.62 IPS |
|
|
Image Segmentation (HP)
|
0
|
||
|
Image Segmentation (Q)
|
0
|
||
|
Pose Estimation (SP)
|
100% |
2791
3.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
810
0.94 IPS |
|
|
Pose Estimation (Q)
|
96% |
719
0.84 IPS |
|
|
Object Detection (SP)
|
100% |
461
36.6 IPS |
|
|
Object Detection (HP)
|
0
|
||
|
Object Detection (Q)
|
0
|
||
|
Face Detection (SP)
|
100% |
909
10.8 IPS |
|
|
Face Detection (HP)
|
100% |
722
8.58 IPS |
|
|
Face Detection (Q)
|
100% |
313
3.72 IPS |
|
|
Depth Estimation (SP)
|
100% |
1415
10.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1074
8.27 IPS |
|
|
Depth Estimation (Q)
|
85% |
685
5.36 IPS |
|
|
Style Transfer (SP)
|
100% |
4257
5.47 IPS |
|
|
Style Transfer (HP)
|
100% |
2841
3.65 IPS |
|
|
Style Transfer (Q)
|
96% |
2247
2.90 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1470
54.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
601
22.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
374
13.8 IPS |
|
|
Text Classification (SP)
|
100% |
475
633.7 IPS |
|
|
Text Classification (HP)
|
100% |
481
641.5 IPS |
|
|
Text Classification (Q)
|
93% |
478
641.5 IPS |
|
|
Machine Translation (SP)
|
100% |
360
6.19 IPS |
|
|
Machine Translation (HP)
|
100% |
561
9.67 IPS |
|
|
Machine Translation (Q)
|
98% |
560
9.68 IPS |
