MacBook Pro (16-inch Late 2019)
Geekbench AI Score
898
Single Precision Score
116
Half Precision Score
92
Quantized Score
Geekbench AI 1.4.0 for macOS AVX2
Result Information
| Upload Date | August 13 2025 06:05 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Intel Core i9-9880H |
| System Information | |
|---|---|
| Operating System | macOS 15.6 (Build 24G84) |
| Model | MacBook Pro (16-inch Late 2019) |
| Model ID | MacBookPro16,1 |
| Motherboard | Apple Inc. Mac-E1008331FDC96864 MacBookPro16,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i9-9880H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
445
82.8 IPS |
|
|
Image Classification (HP)
|
0
|
||
|
Image Classification (Q)
|
0
|
||
|
Image Segmentation (SP)
|
100% |
522
8.46 IPS |
|
|
Image Segmentation (HP)
|
0
|
||
|
Image Segmentation (Q)
|
0
|
||
|
Pose Estimation (SP)
|
100% |
2587
3.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
858
1.00 IPS |
|
|
Pose Estimation (Q)
|
96% |
734
0.86 IPS |
|
|
Object Detection (SP)
|
100% |
466
36.9 IPS |
|
|
Object Detection (HP)
|
0
|
||
|
Object Detection (Q)
|
0
|
||
|
Face Detection (SP)
|
100% |
996
11.8 IPS |
|
|
Face Detection (HP)
|
100% |
836
9.93 IPS |
|
|
Face Detection (Q)
|
100% |
346
4.11 IPS |
|
|
Depth Estimation (SP)
|
100% |
1340
10.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1176
9.06 IPS |
|
|
Depth Estimation (Q)
|
85% |
739
5.78 IPS |
|
|
Style Transfer (SP)
|
100% |
3585
4.61 IPS |
|
|
Style Transfer (HP)
|
100% |
3387
4.35 IPS |
|
|
Style Transfer (Q)
|
96% |
2566
3.31 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1621
59.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
653
24.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
400
14.8 IPS |
|
|
Text Classification (SP)
|
100% |
460
613.5 IPS |
|
|
Text Classification (HP)
|
100% |
469
626.4 IPS |
|
|
Text Classification (Q)
|
93% |
471
631.6 IPS |
|
|
Machine Translation (SP)
|
100% |
343
5.92 IPS |
|
|
Machine Translation (HP)
|
100% |
528
9.09 IPS |
|
|
Machine Translation (Q)
|
98% |
527
9.10 IPS |
